Triple
T8603692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irene Redfield |
E203742
|
entity |
| Predicate | firstAppearance |
P795
|
FINISHED |
| Object | Passing |
E199786
|
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: Passing | Statement: [Irene Redfield, firstAppearance, Passing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Passing Context triple: [Irene Redfield, firstAppearance, Passing]
-
A.
Passing
chosen
"Passing" is a 2021 black-and-white drama film, based on Nella Larsen’s novel, that explores racial identity and colorism in 1920s Harlem.
-
B.
Pass Out
"Pass Out" is a song featured on the album "The Red Light District" by rapper Ludacris.
-
C.
Passabe
Passabe is a village and administrative post in the Oecusse exclave of Timor-Leste, known for its remote location and its role in the region’s political and social history.
-
D.
Passage
Passage is a science fiction novel by Connie Willis that explores near-death experiences through a blend of medical mystery, psychological depth, and dark humor.
-
E.
Winning
"Winning" is a popular rock song by Santana, known for its uplifting lyrics and melodic guitar-driven sound.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46dc23448190a5eb63455578427e |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbb11140819081bde8a1565aad4a |
completed | April 2, 2026, 6:55 p.m. |
Created at: March 30, 2026, 6:24 p.m.