Triple
T28155804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Faris Al-Ghazi |
E714742
|
entity |
| Predicate | collaboratesWithInStory |
P60254
|
FINISHED |
| Object | Special Agent Ronald Fleury |
—
|
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: Special Agent Ronald Fleury | Statement: [Colonel Faris Al-Ghazi, collaboratesWithInStory, Special Agent Ronald Fleury]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collaboratesWithInStory Context triple: [Colonel Faris Al-Ghazi, collaboratesWithInStory, Special Agent Ronald Fleury]
-
A.
partnerInStory
chosen
Indicates that two or more entities are partners or collaborators within the context of a specific story or narrative.
-
B.
collaborationOf
Indicates a relationship in which two or more entities work together jointly toward a shared goal or outcome.
-
C.
associatedWithPersonInStory
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
-
D.
worksOnStoryAbout
Indicates that one entity is actively engaged in creating, developing, or contributing to a story whose subject or focus is another entity.
-
E.
hasCollaboratedIn
Indicates that two or more entities have worked together on a shared project, task, or activity.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 10:02 p.m.