Triple
T6358192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Beckoff |
E143043
|
entity |
| Predicate | conflictTheme |
P5022
|
FINISHED |
| Object | acceptance of her gay son |
—
|
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: acceptance of her gay son | Statement: [Ma Beckoff, conflictTheme, acceptance of her gay son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTheme Context triple: [Ma Beckoff, conflictTheme, acceptance of her gay son]
-
A.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
C.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
D.
settingOfConflict
Indicates the location or context in which a conflict between entities takes place.
-
E.
mainConflict
chosen
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f5bdd481909cf9db595ddb27df |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:32 p.m.