Triple
T12632003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | writing the screenplay of Dirty Harry |
E301665
|
entity |
| Predicate | involvesTask |
P1256
|
FINISHED |
| Object | developing the character of Harry Callahan |
—
|
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: developing the character of Harry Callahan | Statement: [writing the screenplay of Dirty Harry, involvesTask, developing the character of Harry Callahan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesTask Context triple: [writing the screenplay of Dirty Harry, involvesTask, developing the character of Harry Callahan]
-
A.
involves
chosen
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
B.
involvesWorkers
Indicates that an event, process, or situation includes workers as active participants or affected parties.
-
C.
canTask
Indicates that an entity has the ability or permission to perform a specified task.
-
D.
canBeTaskOrganizedWith
Indicates that one entity can be grouped, scheduled, or managed together with another as part of the same task or workflow.
-
E.
involvesIssue
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:15 p.m.