Triple
T8374174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Hunter |
E197532
|
entity |
| Predicate | romanticRelationshipStatus |
P82370
|
FINISHED |
| Object | in an extramarital affair |
—
|
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: in an extramarital affair | Statement: [Frank Hunter, romanticRelationshipStatus, in an extramarital affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticRelationshipStatus Context triple: [Frank Hunter, romanticRelationshipStatus, in an extramarital affair]
-
A.
companionshipStatus
Indicates the current state or condition of a relationship of companionship between two or more entities.
-
B.
relationshipStatusDuringFilm
Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
-
C.
relationshipDurationWith
Indicates the length of time that a specified relationship between two entities has existed or is expected to last.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
spouseOrLover
Indicates a romantic partnership between two entities, whether formalized as a spouse or existing as a lover.
- F. None of above. chosen
Provenance (4 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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80a996ec819083ce2607c0cdab7f |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cd04b08190ab5f72afd22a7967 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6:01 p.m.