Triple
T5962882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olivia Jane Cockburn |
E132680
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Her
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
|
E50437
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Her | Statement: [Olivia Jane Cockburn, knownFor, Her]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Her Context triple: [Olivia Jane Cockburn, knownFor, Her]
-
A.
Her
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
-
B.
Her
"Her" is a lesser-known work by American poet, painter, and City Lights Books co-founder Lawrence Ferlinghetti, reflecting his characteristic Beat-influenced, avant-garde literary style.
-
C.
Her
"Her" is a soulful R&B song by American singer-songwriter SiR, known for its smooth production and introspective lyrics about love and vulnerability.
-
D.
HER
HER is a reinforcement learning technique that improves learning from sparse rewards by reinterpreting failed experiences as successful ones for alternative goals.
-
E.
HER
HER is the commonly used abbreviation for the Harvard Educational Review, a scholarly journal focused on education research and policy.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Her Triple: [Olivia Jane Cockburn, knownFor, Her]
Generated description
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Her Target entity description: Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
-
A.
Her
chosen
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
-
B.
Her
"Her" is a lesser-known work by American poet, painter, and City Lights Books co-founder Lawrence Ferlinghetti, reflecting his characteristic Beat-influenced, avant-garde literary style.
-
C.
Her
"Her" is a soulful R&B song by American singer-songwriter SiR, known for its smooth production and introspective lyrics about love and vulnerability.
-
D.
HER
HER is the official herbarium code assigned to the Berggarten botanical collection, used in scientific and taxonomic references.
-
E.
HER
HER is a reinforcement learning technique that improves learning from sparse rewards by reinterpreting failed experiences as successful ones for alternative goals.
- F. None of above.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03a00e444819087f9df62263e83dc |
completed | March 22, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3ee20648190badedf60a8bc938b |
completed | March 23, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69c0f8d793ac81908e4ce9f867116b0f |
completed | March 23, 2026, 8:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0f94558688190abd771685afa8ebc |
completed | March 23, 2026, 8:26 a.m. |
Created at: March 22, 2026, 4:03 p.m.