Triple
T2382929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jones |
E46350
|
entity |
| Predicate | hasFictionalBearers |
P33843
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jones, hasFictionalBearers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalBearers Context triple: [Jones, hasFictionalBearers, true]
-
A.
hasNotableFictionalBearer
Indicates that an entity is associated with at least one well-known fictional character that bears its name or designation.
-
B.
hasFictionalForm
chosen
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
C.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
D.
fictionalSpecies
Indicates that the subject is a species that exists only in fiction or imaginary works, rather than in real life.
-
E.
hasNotableFieldOfBearers
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7bafa248190a68e8f1e081f4817 |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.