Triple
T863421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love in the Time of Cholera |
E18646
|
entity |
| Predicate | containsCharacterRelationship |
P10690
|
FINISHED |
| Object | love triangle |
—
|
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: love triangle | Statement: [Love in the Time of Cholera, containsCharacterRelationship, love triangle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCharacterRelationship Context triple: [Love in the Time of Cholera, containsCharacterRelationship, love triangle]
-
A.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
B.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
followsCharacter
Indicates that one character moves or acts after another character, maintaining a trailing or subsequent position or sequence relative to them.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6956488190a5644cdd5b55684f |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa86065881909d477e26fdd84d45 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.