Triple
T28437322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of California v. Robert Durst |
E715302
|
entity |
| Predicate | yearOfKillingAlleged |
P181132
|
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: [State of California v. Robert Durst, yearOfKillingAlleged, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfKillingAlleged Context triple: [State of California v. Robert Durst, yearOfKillingAlleged, 2000]
-
A.
lastMurderYear
Indicates the year in which the most recent murder associated with the given entity occurred.
-
B.
estimatedMurdersCommitted
Indicates an approximate count of murders that are believed or inferred to have been committed by an entity.
-
C.
allegedToHaveKilled
Indicates that one entity is claimed or accused, but not proven, to have killed another entity.
-
D.
massacreYear
Indicates the year in which a massacre event took place.
-
E.
numberOfPerpetratorsKilled
Indicates the count of perpetrators who were killed in the context of the described event or incident.
- 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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
| PDg | Predicate description generation | batch_69f762651e088190baa21f25378a6065 |
completed | May 3, 2026, 2:57 p.m. |
Created at: April 28, 2026, 1:43 a.m.