Triple
T5142700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce Willis |
E115996
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bruce |
E52442
|
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: Bruce | Statement: [Bruce Willis, givenName, Bruce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruce Context triple: [Bruce Willis, givenName, Bruce]
-
A.
Bruce
chosen
Bruce is a masculine given name of English and Scottish origin, commonly associated with figures in music, film, and popular culture.
-
B.
Brian
Brian is a masculine given name of Irish origin that has become widely used in English-speaking countries.
-
C.
Bro
Bro is a locality in Stockholm County, Sweden, known as one of the main population centers within Upplands-Bro Municipality.
-
D.
Ben
Ben is a common given name, typically used as a short form of names like Benedict or Benjamin.
-
E.
Brad
Brad is a masculine given name commonly used in English-speaking countries, often as a short form of Bradley or Bradford.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd787ff1c081909a6954aa76e12cbf |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becfec5c108190a3882c25118179a7 |
completed | March 21, 2026, 5:05 p.m. |
Created at: March 20, 2026, 1:43 p.m.