Triple
T4652912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pedro Muzquiz |
E102337
|
entity |
| Predicate | experiencesConflictBetween |
P47733
|
FINISHED |
| Object | marital duty and true love |
—
|
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: marital duty and true love | Statement: [Pedro Muzquiz, experiencesConflictBetween, marital duty and true love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: experiencesConflictBetween Context triple: [Pedro Muzquiz, experiencesConflictBetween, marital duty and true love]
-
A.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
B.
conflictedBetween
chosen
Indicates being torn or uncertain between two or more options, positions, or commitments.
-
C.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
D.
mainConflict
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
E.
addressedConflictWith
Indicates that one entity has taken action to confront, manage, or resolve a conflict involving another entity.
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6314883481908f085a7af497b0d8 |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:14 p.m.