Triple
T7485097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert N. Bellah |
E176860
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Neelly |
E100724
|
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: Neelly | Statement: [Robert N. Bellah, givenName, Neelly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neelly Context triple: [Robert N. Bellah, givenName, Neelly]
-
A.
Neely
chosen
Neely is the surname of Cam Neely, a former professional ice hockey player and current executive best known for his career with the Boston Bruins.
-
B.
Nellie Bellflower
Nellie Bellflower is an American actress and film producer best known for producing the acclaimed 2004 film "Finding Neverland."
-
C.
Nellie Riley
Nellie Riley was the longtime wife of legendary UCLA basketball coach John Wooden and an important personal influence throughout his life and career.
-
D.
Celia Mae
Celia Mae is the one-eyed, snake-haired receptionist at Monsters, Inc. and Mike Wazowski’s girlfriend in the Pixar animated film.
-
E.
Arletta
Arletta, better known as Herleva of Falaise, was the mother of William the Conqueror and a notable figure in 11th-century Norman history.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f53a6bc081909f4b9cd7cdacf045 |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8349d83cc8190af98c3212e28e913 |
completed | March 28, 2026, 8:05 p.m. |
Created at: March 27, 2026, 3:42 p.m.