Triple
T35137511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Batman |
E1014614
|
entity |
| Predicate | hasRoguesGallery |
P197309
|
FINISHED |
| Object | classic Batman villains |
—
|
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: classic Batman villains | Statement: [The Batman, hasRoguesGallery, classic Batman villains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoguesGallery Context triple: [The Batman, hasRoguesGallery, classic Batman villains]
-
A.
hasGallery
Indicates that one entity possesses, contains, or is associated with a gallery, such as a collection or display space.
-
B.
hasNumberOfPaintedGalleries
Indicates the quantity of galleries that have been painted in relation to a given subject.
-
C.
hasArtGallery
Indicates that one entity possesses, contains, or hosts an art gallery as part of its facilities or offerings.
-
D.
hasMuseumComponent
Indicates that something includes, contains, or is composed of a museum or museum-related part as one of its components.
-
E.
hasMuseumOrTreasureHouse
Indicates that an entity contains, hosts, or is associated with a museum or treasure house.
- 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_69f76dd9c1848190af70d4882a2c1ad7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
| PDg | Predicate description generation | batch_69fe86c98d688190a99d5dcb14e2dc95 |
completed | May 9, 2026, 12:58 a.m. |
Created at: May 3, 2026, 4:02 p.m.