Triple
T25193389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Darabont |
E630936
|
entity |
| Predicate | basedManyWorksOn |
P161445
|
FINISHED |
| Object | Stephen King stories |
—
|
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: Stephen King stories | Statement: [Frank Darabont, basedManyWorksOn, Stephen King stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedManyWorksOn Context triple: [Frank Darabont, basedManyWorksOn, Stephen King stories]
-
A.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
B.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
-
C.
basedOnManyProjects
Indicates that something is derived from, influenced by, or constructed using multiple underlying projects.
-
D.
workTypeContributedTo
Indicates that an entity contributed to the creation, development, or production of a particular type of work.
-
E.
hasCreatedWorksFor
Indicates that one entity has produced or created works (such as art, documents, or products) on behalf of or for the benefit of another entity.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f613502d808190b89927e5e734b43a |
completed | May 2, 2026, 3:08 p.m. |
Created at: April 21, 2026, 12:45 p.m.