Triple
T13350991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conrad Vig |
E318066
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Troy Barlow |
E369465
|
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: Troy Barlow | Statement: [Conrad Vig, associatedWith, Troy Barlow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troy Barlow Context triple: [Conrad Vig, associatedWith, Troy Barlow]
-
A.
Troy Barlow
chosen
Troy Barlow is a U.S. Army reservist and one of the central soldiers in the 1999 war film "Three Kings," portrayed by Mark Wahlberg.
-
B.
Troy Buswell
Troy Buswell is an Australian politician who served in senior roles in Western Australia's state government, including as Treasurer.
-
C.
Troy Verges
Troy Verges is an American songwriter and record producer known for his work in contemporary country and pop music.
-
D.
Troy Dannen
Troy Dannen is a collegiate sports executive who serves as the athletic director for the University of Washington Huskies, overseeing the school's athletic programs and operations.
-
E.
Scott Barlow
Scott Barlow is an Australian businessman best known for his long-term leadership role as chairman and major stakeholder of A-League football club Sydney FC.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b058bc688190b3549d1cac6f4576 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 9:31 p.m.