Triple
T20007411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velvet |
E494493
|
entity |
| Predicate | hasSeamstressProtagonist |
P138343
|
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: [Velvet, hasSeamstressProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeamstressProtagonist Context triple: [Velvet, hasSeamstressProtagonist, true]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
D.
hasNotableTailor
Indicates that an entity is associated with a tailor who is distinguished or noteworthy in some significant way.
-
E.
protagonistMust
Indicates that a particular entity is required to serve as the main character or central focus within a narrative or scenario.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a648a88190853ee741edcf6ca2 |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:33 p.m.