Triple
T6421597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian France |
E127955
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Brian |
E87241
|
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: Brian | Statement: [Brian France, givenName, Brian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Context triple: [Brian France, givenName, Brian]
-
A.
Brian
chosen
Brian is a masculine given name of Irish origin that has become widely used in English-speaking countries.
-
B.
Brad
Brad is a masculine given name commonly used in English-speaking countries, often as a short form of Bradley or Bradford.
-
C.
Bruce
Bruce is a masculine given name of English and Scottish origin, commonly associated with figures in music, film, and popular culture.
-
D.
Ben
Ben is a common given name, typically used as a short form of names like Benedict or Benjamin.
-
E.
Neil
Neil is a central character in Mary Higgins Clark's suspense novel "A Stranger Is Watching," around whom much of the kidnapping and tension-filled plot revolves.
- 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06903f67c8190a1e5babeede4e183 |
completed | March 22, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640d8f7548190a8e0433df56b77f3 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:43 p.m.