Triple
T3528512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanda Miller |
E74598
|
entity |
| Predicate | relationshipToKennyRogers |
P10690
|
FINISHED |
| Object | fourth wife |
—
|
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: fourth wife | Statement: [Wanda Miller, relationshipToKennyRogers, fourth wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKennyRogers Context triple: [Wanda Miller, relationshipToKennyRogers, fourth wife]
-
A.
relationshipToLaurie
Indicates the specific type of relationship or connection that an entity has to Laurie.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
D.
relationshipPlannedWith
Indicates that a relationship between two entities has been intentionally arranged or scheduled to occur in the future.
-
E.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6e9188819093480b39f263ce75 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.