Triple
T9057810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisco Houston |
E217047
|
entity |
| Predicate | givenName |
P17
|
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: [Cisco Houston, givenName, Gilbert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilbert Context triple: [Cisco Houston, givenName, 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.
Gilbert
Gilbert is a renowned sports equipment manufacturer best known for producing high-quality rugby balls used in major international competitions.
-
D.
Niles
Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
-
E.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ec808bc8190957b80820d98fd5b |
completed | April 1, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebe40ec08190a1da2aa1c6577723 |
completed | April 3, 2026, 4:33 p.m. |
Created at: March 30, 2026, 7:10 p.m.