Triple
T7731192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Rogers |
E175258
|
entity |
| Predicate | isCharacterInSetting |
P78408
|
FINISHED |
| Object | 19th-century American town |
—
|
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: 19th-century American town | Statement: [Ben Rogers, isCharacterInSetting, 19th-century American town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCharacterInSetting Context triple: [Ben Rogers, isCharacterInSetting, 19th-century American town]
-
A.
characterStatusInStory
Indicates the role or condition a character holds within the context of a specific story or narrative.
-
B.
isCharacterInWorkLanguage
Indicates that a character appears in a work (e.g., book, film, game) in a specific language version or localization.
-
C.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
D.
isCharacterInCountryOfOrigin
Indicates that a character is located within or associated with their original country of origin.
-
E.
isClericIn
Indicates that an entity serves or functions as a cleric within a specified organization, location, or group.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c7016c4a748190a7012030edaefcee |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c7040091608190a9e46ecfb2ff0bca |
completed | March 27, 2026, 10:26 p.m. |
Created at: March 27, 2026, 4:06 p.m.