Triple
T824093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenAI Baselines |
E17813
|
entity |
| Predicate | implementsAlgorithm |
P8649
|
FINISHED |
| Object | HER |
E50437
|
NE FINISHED |
How this triple was built (2 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: [OpenAI Baselines, implementsAlgorithm, HER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HER Context triple: [OpenAI Baselines, implementsAlgorithm, HER]
-
A.
HER
HER is the commonly used abbreviation for the Harvard Educational Review, a scholarly journal focused on education research and policy.
-
B.
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.
-
C.
HES
HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
-
D.
HM
HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
-
E.
Hor
Hor is an abbreviated form of the name Horace, often used as a short or familiar version of it.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b503d48190bd4f33548a22d5fe |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d93af548190818c14a370e0914a |
completed | March 3, 2026, 11:24 p.m. |
Created at: March 1, 2026, 7:38 p.m.