Triple
T35801161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Paul Steuer |
E1034980
|
entity |
| Predicate | characterInGraceUnderFire |
P12208
|
FINISHED |
| Object | Quentin Kelly |
—
|
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: Quentin Kelly | Statement: [Jon Paul Steuer, characterInGraceUnderFire, Quentin Kelly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInGraceUnderFire Context triple: [Jon Paul Steuer, characterInGraceUnderFire, Quentin Kelly]
-
A.
characterIn
chosen
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
B.
characterInConflict
Indicates a relationship where a character is engaged in opposition, struggle, or disagreement with another force, character, or situation.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
crewCharacterization
Indicates how the crew of an entity (such as a vessel, vehicle, or facility) is described or classified in terms of its composition, qualities, or role.
-
E.
characterInFocus
Indicates that a particular character is the primary subject or focal point within a given context, scene, or narrative segment.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffab5adf2c819084700c5ea34615bf |
completed | May 9, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69ffaabffa208190b5214ca17cc8a5ea |
completed | May 9, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:06 p.m.