Triple
T30335839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | murder of Nancy Montgomery |
E771617
|
entity |
| Predicate | employerOfVictim |
P7
|
FINISHED |
| Object | Thomas Kinnear |
—
|
NE NERFINISHED |
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: Thomas Kinnear | Statement: [murder of Nancy Montgomery, employerOfVictim, Thomas Kinnear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerOfVictim Context triple: [murder of Nancy Montgomery, employerOfVictim, Thomas Kinnear]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
victimOccupation
Indicates the profession or job role held by the person who is the victim in an event or incident.
-
C.
employer
chosen
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
-
D.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
-
E.
employerDefendantIn
Indicates that the employer of a person or entity is a named defendant in a legal case or proceeding.
- 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 29, 2026, 7:54 p.m.