Triple
T33898412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Greenhalgh |
E868978
|
entity |
| Predicate | basedOnRealPersonInWork |
P54368
|
FINISHED |
| Object | Ian Curtis – Control |
—
|
NE NERFINISHED |
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: Ian Curtis – Control | Statement: [Matt Greenhalgh, basedOnRealPersonInWork, Ian Curtis – Control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnRealPersonInWork Context triple: [Matt Greenhalgh, basedOnRealPersonInWork, Ian Curtis – Control]
-
A.
basedOnRealPersonFor
chosen
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
-
B.
realPerson
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
C.
basedOnWorkDirector
Indicates that one entity serves as the director of a work on which another entity is based.
-
D.
humanRepresentative
Indicates that one entity serves as a human agent or delegate acting on behalf of another entity.
-
E.
hasOccupationInReality
Indicates that an entity holds or performs a specific occupation in the real world, as opposed to fictional or hypothetical contexts.
- F. None of above.
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_69f34997703c8190866b1d404bce531f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 1, 2026, 1:48 a.m.