Triple
T37960046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Winter: A Film by Dick Pierre |
E946981
|
entity |
| Predicate | hasFictionalDirectorCharacter |
P202392
|
FINISHED |
| Object | Dick Pierre |
—
|
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: Dick Pierre | Statement: [Hot Winter: A Film by Dick Pierre, hasFictionalDirectorCharacter, Dick Pierre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalDirectorCharacter Context triple: [Hot Winter: A Film by Dick Pierre, hasFictionalDirectorCharacter, Dick Pierre]
-
A.
hasFictionalLeadCharacter
Indicates that a creative work features a particular fictional character as its main or leading protagonist.
-
B.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
C.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
D.
hasFictionalSpeaker
Indicates that a work, text, or expression is presented as being spoken by an invented or non-real speaker rather than an actual person.
-
E.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
- 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a007899cadc8190a04edd503eaf6514 |
completed | May 10, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_6a0078493e088190b0c5047cbe75d304 |
completed | May 10, 2026, 12:21 p.m. |
| PDg | Predicate description generation | batch_6a00789927708190b031d3a9d5f4f68e |
completed | May 10, 2026, 12:22 p.m. |
Created at: May 3, 2026, 4:20 p.m.