Triple
T15493454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilson Fisk |
E378752
|
entity |
| Predicate | hasBodyguard |
P957
|
FINISHED |
| Object | Bullseye |
E906127
|
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: Bullseye | Statement: [Wilson Fisk, hasBodyguard, Bullseye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bullseye Context triple: [Wilson Fisk, hasBodyguard, Bullseye]
-
A.
Bullseye
Bullseye is a British television game show that combines darts with general knowledge quizzes, originally popular in the 1980s and 1990s.
-
B.
Bullseye
chosen
Bullseye is a deadly Marvel Comics assassin and frequent Daredevil adversary known for his uncanny ability to turn almost any object into a lethal projectile.
-
C.
Bullseye
Bullseye is Woody’s loyal toy horse in the Toy Story franchise, known for his expressive, nonverbal personality and close bond with the other toys.
-
D.
Bullseye
"Bullseye" is a thriller novel in James Patterson and Michael Ledwidge's Michael Bennett series, following the NYPD detective as he races to stop an assassination plot against the U.S. president.
-
E.
Shooting Gallery
Shooting Gallery is a film distribution company known for handling and releasing independent and art-house movies.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fad723481908d2aa33e8f065f2f |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3660fc6c81908caf1729260a8338 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:49 a.m.