Triple
T33775883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marianne |
E865515
|
entity |
| Predicate | primaryConflictInvolves |
P5022
|
FINISHED |
| Object | cursed red dress |
—
|
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: cursed red dress | Statement: [Marianne, primaryConflictInvolves, cursed red dress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryConflictInvolves Context triple: [Marianne, primaryConflictInvolves, cursed red dress]
-
A.
mainConflict
chosen
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
B.
centralConflictIn
Indicates that one situation, issue, or opposition serves as the primary source of tension or struggle within another context, such as a story, event, or scenario.
-
C.
secondaryConflict
Indicates a secondary or subordinate conflict that arises in addition to a primary or main conflict between entities.
-
D.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
E.
typicalConflict
Indicates that there is a commonly occurring or characteristic conflict or opposition between the related entities.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:45 a.m.