Triple
T18690927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trabucco |
E456996
|
entity |
| Predicate | dynamicWithVictorClooney |
P132293
|
FINISHED |
| Object | comic contrast |
—
|
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: comic contrast | Statement: [Trabucco, dynamicWithVictorClooney, comic contrast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dynamicWithVictorClooney Context triple: [Trabucco, dynamicWithVictorClooney, comic contrast]
-
A.
isFianceeOf
Indicates that one person is the engaged-to-be-married partner of another person.
-
B.
victor
Indicates that one entity is the winner or has prevailed over another in a contest, conflict, or competition.
-
C.
formerFiancéeOf
Indicates that one person was previously engaged to be married to another person, but the engagement has since ended.
-
D.
Lincoln Lewis
Indicates a relationship or association involving the entity or name "Lincoln Lewis," such as authorship, participation, or attribution in a given context.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- F. None of above. chosen
Provenance (4 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e3a6d08190b2409bcbf0c42444 |
completed | April 19, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484133ee48190a80f1889d79f34c9 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:49 a.m.