Triple
T33403316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine (ex‑wife) |
E855371
|
entity |
| Predicate | conflictTypeWithTheodore |
P1397
|
FINISHED |
| Object | emotional incompatibility |
—
|
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: emotional incompatibility | Statement: [Catherine (ex‑wife), conflictTypeWithTheodore, emotional incompatibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTypeWithTheodore Context triple: [Catherine (ex‑wife), conflictTypeWithTheodore, emotional incompatibility]
-
A.
conflictDescribedIn
Indicates that a particular conflict is documented, detailed, or discussed within a specified information source or description.
-
B.
facedConflictOver
Indicates that two or more entities experienced opposition, dispute, or tension concerning a particular issue, resource, or situation.
-
C.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
D.
hasIdeologicalConflict
Indicates a relationship where two entities hold opposing or incompatible ideologies that put them in conflict with each other.
-
E.
conflictTopic
Indicates that the entities are in conflict specifically regarding the referenced topic or issue.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:36 a.m.