Triple
T19307040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicol Stephen |
E482858
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nicol |
—
|
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: Nicol | Statement: [Nicol Stephen, givenName, Nicol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicol Context triple: [Nicol Stephen, givenName, Nicol]
-
A.
Nicol
chosen
Nicol is a Scottish surname most notably associated with former professional footballer and manager Steve Nicol.
-
B.
Nichola
Nichola is a feminine given name of Greek origin, commonly considered a variant of Nicola or Nicholas and used in English-speaking countries.
-
C.
Nika
Nika is the given first name of American singer, songwriter, and producer Zola Jesus (Nika Roza Danilova).
-
D.
Nicole
Nicole is a sharp-tongued, down-to-earth maid in Molière’s comedy "Le Bourgeois gentilhomme," often serving as a voice of reason and satire against her master’s pretensions.
-
E.
Nicole
Nicole is a central character in the dark comedy-drama film "Hesher," serving as a key emotional anchor in the story’s exploration of grief and unconventional relationships.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604ca81e88190a276064f5f8dfd3a |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 10, 2026, 1:32 p.m.