Triple
T6731093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff "Joker" Moreau |
E153633
|
entity |
| Predicate | hasDisabilityRepresentation |
P73408
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Jeff "Joker" Moreau, hasDisabilityRepresentation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisabilityRepresentation Context triple: [Jeff "Joker" Moreau, hasDisabilityRepresentation, yes]
-
A.
causeOfDisability
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
B.
disability
Indicates that an entity has a physical, mental, or sensory impairment that substantially limits one or more major life activities.
-
C.
usesWheelchair
Indicates that an entity relies on or operates a wheelchair for mobility or transportation.
-
D.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
E.
hasDisabledAccess
Indicates that an entity provides facilities, features, or accommodations that make it accessible to people with disabilities.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d35134148190b49fb5c25a0f8ed4 |
completed | March 27, 2026, 6:58 p.m. |
Created at: March 27, 2026, 2:09 p.m.