Triple
T13100480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coy Gibbs |
E310704
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Coy |
E620295
|
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: Coy | Statement: [Coy Gibbs, givenName, Coy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coy Context triple: [Coy Gibbs, givenName, Coy]
-
A.
Coy
chosen
Coy is a given name that can be used for individuals of any gender, often appearing in English-speaking contexts.
-
B.
Coo
Coo is a small village in the Belgian Ardennes known for its waterfall and nearby amusement attractions.
-
C.
Coby
Coby is a given name commonly used as a diminutive or nickname, particularly for names like Jacoba or Jacob.
-
D.
Cooney
Cooney is a surname most notably associated with Gerry Cooney, an American former professional heavyweight boxer known for his powerful punching.
-
E.
Conoley
Conoley is the surname of Jane Close Conoley, an American psychologist and academic administrator known for serving as president of California State University, Long Beach.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981515d488190908d3cca1b84a42d |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d61bcfe88190866b4330d1669602 |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:04 p.m.