Triple
T27941422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radley Tate |
E700757
|
entity |
| Predicate | mainCharacterAssociated |
P88683
|
FINISHED |
| Object | Carla Tate |
—
|
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: Carla Tate | Statement: [Radley Tate, mainCharacterAssociated, Carla Tate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterAssociated Context triple: [Radley Tate, mainCharacterAssociated, Carla Tate]
-
A.
mainCharacterField
Indicates that one entity is designated as the primary or central character associated with another entity, such as a work or narrative.
-
B.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
C.
mainCharacterAffiliation
Indicates the group, organization, or side with which the main character is formally or primarily aligned.
-
D.
fictionalCharacterAssociatedWith
chosen
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
E.
mainMortalCharacter
Indicates that the referenced entity serves as the primary mortal (non-immortal) character in the context of a story or narrative.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 27, 2026, 7:18 p.m.