Triple
T31001790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Graham, Baron Lynedoch |
E789958
|
entity |
| Predicate | causeOfMilitaryCareer |
P182261
|
FINISHED |
| Object | death of his wife Mary Cathcart |
—
|
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: death of his wife Mary Cathcart | Statement: [Thomas Graham, Baron Lynedoch, causeOfMilitaryCareer, death of his wife Mary Cathcart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfMilitaryCareer Context triple: [Thomas Graham, Baron Lynedoch, causeOfMilitaryCareer, death of his wife Mary Cathcart]
-
A.
causeOfEndOfMilitaryCareer
Indicates the event, condition, or factor that brought about the termination of an entity’s military career.
-
B.
reasonForEnlistment
Indicates the motivation, cause, or circumstances that led an individual to join a military or similar organized service.
-
C.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
D.
favoredMilitaryRole
Indicates the military position, function, or specialization that an entity prefers or is most inclined to choose.
-
E.
postMilitaryCareer
Indicates that one entity’s career or occupation occurs after the completion of their military service.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7886b27f08190ab4580f949222c93 |
completed | May 3, 2026, 5:39 p.m. |
Created at: April 29, 2026, 8:56 p.m.