Triple
T29539829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | There Was a Crooked Man |
E749460
|
entity |
| Predicate | primaryCharacterType |
P20969
|
FINISHED |
| Object | comic protagonist |
—
|
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: comic protagonist | Statement: [There Was a Crooked Man, primaryCharacterType, comic protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCharacterType Context triple: [There Was a Crooked Man, primaryCharacterType, comic protagonist]
-
A.
protagonistType
chosen
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
B.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
C.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
D.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a013e23698c81909a32d371b6f158d0 |
completed | May 11, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_6a013db04b108190985897aa6e95b4ec |
completed | May 11, 2026, 2:23 a.m. |
Created at: April 28, 2026, 5:01 p.m.