Triple
T12775741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce McCleery |
E305365
|
entity |
| Predicate | roleInSabotage |
P106847
|
FINISHED |
| Object | cinematographer |
—
|
LITERAL 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: cinematographer | Statement: [Bruce McCleery, roleInSabotage, cinematographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInSabotage Context triple: [Bruce McCleery, roleInSabotage, cinematographer]
-
A.
roleInMutiny
Indicates that one entity participated in a mutiny with a specific role or capacity in that rebellious action.
-
B.
roleInCrime
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
C.
terroristRole
Indicates that an entity plays a specific functional role within a terrorist organization or terrorist activity.
-
D.
roleInOperationJustCause
Indicates that an entity participated in or held a specific role during Operation Just Cause.
-
E.
wasFoiledBy
Indicates that an attempted action, plan, or goal was prevented or thwarted by another entity.
- F. None of above. chosen
Provenance (4 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df6b3c88190b0bbe70de8ddcbf3 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:29 p.m.