Triple
T1662412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rod Gilbert |
E35937
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gilbert |
E88415
|
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: Gilbert | Statement: [Rod Gilbert, familyName, Gilbert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilbert Context triple: [Rod Gilbert, familyName, Gilbert]
-
A.
Gilbert
Gilbert is a rapidly growing suburban town in the southeastern Phoenix metropolitan area known for its family-friendly communities and high quality of life.
-
B.
Gilbert
chosen
Gilbert is a masculine given name of Norman-French origin that has been borne by various notable figures, including philosophers, writers, and entertainers.
-
C.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
-
D.
Hayden
Hayden is a surname most notably associated with American actor and author Sterling Hayden, known for his roles in classic mid-20th-century films.
-
E.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90ab3bd7081908d15d772b10aebbe |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad682ab8a08190bdb33d79d5083029 |
completed | March 8, 2026, 12:14 p.m. |
Created at: March 4, 2026, 7:29 p.m.