Triple
T12069434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicki Collen |
E287383
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Collen |
E287383
|
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: Collen | Statement: [Nicki Collen, familyName, Collen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Collen Context triple: [Nicki Collen, familyName, Collen]
-
A.
Collen
chosen
Collen is a surname most notably associated with Nicki Collen, an American basketball coach.
-
B.
Collin
Collin is a masculine given name, often considered a variant of Colin, used in English-speaking countries.
-
C.
Collett
Collett is the surname of Australian actress and producer Toni Collette, known for her versatile performances in film, television, and theatre.
-
D.
Rennahan
Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
-
E.
Dillon
Dillon is a small city in southwestern Montana known as a regional hub for ranching, outdoor recreation, and as the home of the University of Montana Western.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90457fd488190b311ed69d2aebdf9 |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f65af0e88190ad32adb9ff76b01b |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.