Triple
T36879639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Two-Gun Man |
E911439
|
entity |
| Predicate | featureCharacterType |
P93957
|
FINISHED |
| Object | cowboy hero |
—
|
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: cowboy hero | Statement: [The Two-Gun Man, featureCharacterType, cowboy hero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureCharacterType Context triple: [The Two-Gun Man, featureCharacterType, cowboy hero]
-
A.
featuresCharacterWith
chosen
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
B.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
C.
helpsCharacterType
Indicates that one character type provides assistance or support to another character type.
-
D.
employsCharacterType
Indicates that an entity makes use of or features a particular type or category of character in its content or structure.
-
E.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
- 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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.