Triple
T1408372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Kruger |
E31747
|
entity |
| Predicate | startTimeOfPartnerNormanReedus |
P26593
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Diane Kruger, startTimeOfPartnerNormanReedus, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfPartnerNormanReedus Context triple: [Diane Kruger, startTimeOfPartnerNormanReedus, 2016]
-
A.
startTimeAsNFLReferee
Indicates the point in time when an individual began serving in the role of an NFL referee.
-
B.
startTimeAsRepresentative
Indicates the time at which an entity begins serving or acting in a representative capacity.
-
C.
startTimeForPosition_AssociateJustice
Indicates the date and time at which an individual begins serving in the role of Associate Justice.
-
D.
startTimeAsMemberOfRamones
Indicates the time at which an individual first became a member of the Ramones.
-
E.
startTimeOfNFLOfficiatingCareer
Indicates the point in time when an individual's NFL officiating career 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bf7f0c8190aee96818de6ff4a5 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:59 p.m.