Triple
T15193931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heroes and Villains |
E363095
|
entity |
| Predicate | hasMultipleSections |
P62241
|
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: [Heroes and Villains, hasMultipleSections, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleSections Context triple: [Heroes and Villains, hasMultipleSections, true]
-
A.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
B.
hasVerticalSection
Indicates that one entity possesses or includes a distinct vertical section or segment as part of its structure or representation.
-
C.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
D.
hasCollectionSection
Indicates that an entity includes or is organized into a specific section within a larger collection.
-
E.
hasMultiple
chosen
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067eb710819085211fd05d5fa5f0 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:10 a.m.