Triple
T29683435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sick Boy |
E751017
|
entity |
| Predicate | filmScreenwriterOfWorkHeAppearsIn |
P109914
|
FINISHED |
| Object | John Hodge |
—
|
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: John Hodge | Statement: [Sick Boy, filmScreenwriterOfWorkHeAppearsIn, John Hodge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmScreenwriterOfWorkHeAppearsIn Context triple: [Sick Boy, filmScreenwriterOfWorkHeAppearsIn, John Hodge]
-
A.
screenwriterOfWorkAppearsIn
Indicates that a person is the screenwriter of a work in which they themselves also appear.
-
B.
screenwriterOfWorkAppearingIn
Indicates that a person is the screenwriter of a work in which a specified entity (such as a character, actor, or role) appears.
-
C.
filmWriterOfWorkAppearedIn
chosen
Indicates that a person is the writer of a film in which they themselves also appeared (e.g., as an actor or on-screen participant).
-
D.
screenwriterOfWorkFeaturing
Indicates that one entity is the screenwriter responsible for creating the screenplay for a work in which the other entity appears or is featured.
-
E.
screenwriterOfWork
Indicates that a person served as the screenwriter (wrote the screenplay) for a particular creative work.
- 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f6728d8d8881909cc97dd523866934 |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:11 p.m.