Triple
T21502863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Engelman |
E530522
|
entity |
| Predicate | roleInMysteryMen |
P144647
|
FINISHED |
| Object | producer |
—
|
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: producer | Statement: [Robert Engelman, roleInMysteryMen, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInMysteryMen Context triple: [Robert Engelman, roleInMysteryMen, producer]
-
A.
roleInWatchmen
Indicates that one entity has a specific role or function within the context of the work "Watchmen" in relation to the other entity.
-
B.
roleInMurderOnTheOrientExpress
Indicates the specific involvement or function an entity has within the context of the murder case in "Murder on the Orient Express."
-
C.
roleInSherlock
Indicates the specific role or character that an entity portrays or holds in the context of the Sherlock series or franchise.
-
D.
roleInComics
Indicates that an entity holds a specific role or function within the context of comic books or comic-related works.
-
E.
roleInInvestigation
Indicates that an entity holds a specific function, capacity, or responsibility within the context of a particular investigation.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5deb388190a89a1f94285b7e55 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:24 p.m.