Triple
T13933582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sacrifice |
E335051
|
entity |
| Predicate | characterRoleOfPaulaPatton |
P94795
|
FINISHED |
| Object | criminal psychologist |
—
|
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: criminal psychologist | Statement: [Sacrifice, characterRoleOfPaulaPatton, criminal psychologist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfPaulaPatton Context triple: [Sacrifice, characterRoleOfPaulaPatton, criminal psychologist]
-
A.
roleOfPaula
Indicates that Paula holds or performs a specific role or function in relation to another entity or context.
-
B.
performerCharacterName
chosen
Indicates that a performer is associated with or portrays a specific character name in a performance or work.
-
C.
roleOfPatriceWilson
Indicates that Patrice Wilson serves in a particular role or capacity in relation to another entity.
-
D.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
E.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf28df081908d897d7b9ec7939d |
completed | April 14, 2026, 12:02 p.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.