Triple
T3706284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Williams |
E80901
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bernard |
E24525
|
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: Bernard | Statement: [Bernard Williams, givenName, Bernard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernard Context triple: [Bernard Williams, givenName, Bernard]
-
A.
Bernard
chosen
Bernard is a masculine given name of Old French and Germanic origin, historically borne by notable figures such as military leaders and saints.
-
B.
Alain
Alain is a masculine given name of French origin, derived from the Breton name Alan and widely used in French-speaking countries.
-
C.
Gerald
Gerald is the birth name of Jerry Brown, the longtime Democratic politician and former governor of California.
-
D.
Gerald
Gerald is the middle name of Stephen G. Breyer, a former Associate Justice of the United States Supreme Court.
-
E.
Gerald
Gerald is a masculine given name of Germanic origin, commonly used in English-speaking countries.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54ce1788190ac000793cbdaba48 |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdfe77a481908880d0a4a5946656 |
completed | March 14, 2026, 2:54 a.m. |
Created at: March 8, 2026, 3:33 p.m.