Triple
T19407716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecca Luker |
E485505
|
entity |
| Predicate | marriageToDannyBursteinStart |
P135759
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Rebecca Luker, marriageToDannyBursteinStart, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageToDannyBursteinStart Context triple: [Rebecca Luker, marriageToDannyBursteinStart, 2000]
-
A.
marriageStartWithRobReiner
Indicates the point in time when an entity begins a marital relationship with Rob Reiner.
-
B.
startTime (marriage to Liza Minnelli)
Indicates the date and time when the marriage to Liza Minnelli began.
-
C.
marriedToArthurMillerBefore
Indicates that a person was married to Arthur Miller at some time prior to a specified reference point or event.
-
D.
startTimeOfMarriageToBillMurray
Indicates the point in time when an individual’s marriage to Bill Murray began.
-
E.
marriageToHenryFondaStart
Indicates the point in time when an entity’s marriage to Henry Fonda began.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257bad0c819088dd7729b6a36a94 |
completed | April 20, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:36 p.m.