Triple
T15025341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristen Mary Houghton |
E378196
|
entity |
| Predicate | startTimeOfSpouseRelationshipWith Caitlyn Jenner |
P14428
|
FINISHED |
| Object | 1991 |
—
|
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: 1991 | Statement: [Kristen Mary Houghton, startTimeOfSpouseRelationshipWith Caitlyn Jenner, 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfSpouseRelationshipWith Caitlyn Jenner Context triple: [Kristen Mary Houghton, startTimeOfSpouseRelationshipWith Caitlyn Jenner, 1991]
-
A.
spouseStartTime
chosen
Indicates the point in time when two individuals began their spousal (marriage) relationship.
-
B.
startTime_spouse_John_McCain
Indicates the time at which John McCain’s spousal relationship with a given person began.
-
C.
spouseOfSince
Indicates that two individuals are spouses and specifies the date or time from which their marital relationship has been in effect.
-
D.
spousePositionHeldStartTime
Indicates the date and time when a spouse first began holding a particular position or office.
-
E.
metSpouseAt
Indicates that one person first encountered or became acquainted with their spouse at a particular place, event, or time.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7dfcb508190aec8cd667e27a8ea |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:57 a.m.