Triple
T18945428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spencer James |
E463500
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Coop |
—
|
NE NERFINISHED |
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: Coop | Statement: [Spencer James, closeFriend, Coop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coop Context triple: [Spencer James, closeFriend, Coop]
-
A.
Coop
Coop is a central character in the work "Divisadero," around whom much of the story’s emotional and narrative focus revolves.
-
B.
The Coop
The Coop is a historic, student-run cooperative bookstore and general store serving the Harvard University community in Cambridge, Massachusetts.
-
C.
The Coop
The Coop is the nickname for Cooper Stadium, a former minor league baseball park in Columbus, Ohio that long served as the home of the Columbus Clippers.
-
D.
Coopernook
Coopernook is a small rural village in New South Wales, Australia, known for its farming community and location near the Lansdowne River and coastal forests.
-
E.
Koop
Koop is a surname most prominently associated with C. Everett Koop, the influential former Surgeon General of the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d53f6eb8819099b1268db8b14d66 |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 10, 2026, 11:59 a.m.