Triple
T24771625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. James Warwick |
E619739
|
entity |
| Predicate | treatedCharacter |
P44049
|
FINISHED |
| Object | Taylor Hayes |
—
|
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: Taylor Hayes | Statement: [Dr. James Warwick, treatedCharacter, Taylor Hayes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatedCharacter Context triple: [Dr. James Warwick, treatedCharacter, Taylor Hayes]
-
A.
treatsCharacter
chosen
Indicates how one character behaves toward or interacts with another character, especially in terms of care, respect, or mistreatment.
-
B.
treatmentCharacterization
Indicates how a treatment is defined, described, or categorized in terms of its nature, properties, or distinguishing features.
-
C.
allyOfCharacter
Indicates that one character maintains an alliance or supportive partnership with another character.
-
D.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410abf6588190ac997f02a1177c19 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:31 a.m.