Triple
T21502865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Engelman |
E530522
|
entity |
| Predicate | roleInThinner |
P144648
|
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, roleInThinner, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInThinner Context triple: [Robert Engelman, roleInThinner, producer]
-
A.
roleInName
Indicates that a specific role, title, or position is included as part of an entity’s name or naming expression.
-
B.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
C.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
D.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
E.
roleInSilhouette
Indicates that an entity has a specific functional or positional role within a larger silhouette or outline structure.
- 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.