Triple
T26989324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Universe 1985 |
E679822
|
entity |
| Predicate | congeniality |
P37384
|
FINISHED |
| Object | Brigitte Bergman |
—
|
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: Brigitte Bergman | Statement: [Miss Universe 1985, congeniality, Brigitte Bergman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: congeniality Context triple: [Miss Universe 1985, congeniality, Brigitte Bergman]
-
A.
arity
Indicates the number of arguments or participants that a relation or function takes.
-
B.
isSympatheticTo
Indicates that one entity feels or expresses compassion, understanding, or emotional support toward another entity.
-
C.
ability
Indicates that an entity has the capacity or power to perform a particular action or achieve a specific outcome.
-
D.
attitudeTowardOthers
Indicates the nature or disposition of one entity’s feelings, judgments, or behavioral stance toward other entities.
-
E.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6218de4ec81908d3001e5b8748c7d |
completed | May 2, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69f611b07a808190af7c704bbdfe0587 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:50 a.m.