Triple
T11498490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Callery |
E272604
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bones |
E328563
|
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: Bones | Statement: [Sean Callery, notableWork, Bones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bones Context triple: [Sean Callery, notableWork, Bones]
-
A.
Bones
Bones is the nickname of Bones McKinney, a notable American basketball player and coach from the mid-20th century.
-
B.
Bones
chosen
Bones is a 2001 supernatural horror film starring Snoop Dogg as a murdered man who returns from the dead to exact revenge.
-
C.
Bones
"Bones" is the official theme song used for WWE's WrestleMania 29 event.
-
D.
Bones
Bones is a popular American crime procedural television series that blends forensic anthropology with FBI investigations, following Dr. Temperance Brennan and Agent Seeley Booth as they solve murders using skeletal evidence.
-
E.
Bones
Bones is the nickname of Dr. Leonard McCoy, the irascible yet compassionate chief medical officer aboard the starship Enterprise in the Star Trek franchise.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de27db081909ccdb4ab0ef75bdb |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e604aa9e3c8190ad86e4d05a67c8ac |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 8, 2026, 9:36 p.m.