Triple
T10364109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Micky Ward |
E244206
|
entity |
| Predicate | hasFictionalRepresentation |
P33843
|
FINISHED |
| Object | Charlene Fleming’s boyfriend in The Fighter |
—
|
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: Charlene Fleming’s boyfriend in The Fighter | Statement: [Micky Ward, hasFictionalRepresentation, Charlene Fleming’s boyfriend in The Fighter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalRepresentation Context triple: [Micky Ward, hasFictionalRepresentation, Charlene Fleming’s boyfriend in The Fighter]
-
A.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
B.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
C.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
D.
hasFictionalForm
chosen
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
E.
portraysFictionalEntity
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e963a6148190822951e72590b9df |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, noon