Triple
T544834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Headless Horseman |
E12709
|
entity |
| Predicate | occupationInLife |
P2374
|
FINISHED |
| Object | Hessian trooper |
—
|
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: Hessian trooper | Statement: [Headless Horseman, occupationInLife, Hessian trooper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationInLife Context triple: [Headless Horseman, occupationInLife, Hessian trooper]
-
A.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
vocationType
Indicates the specific kind or category of occupation, profession, or calling associated with an entity.
-
C.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
D.
settingOfWork
Indicates the place, time, or environment in which a creative work’s narrative or events are situated.
-
E.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a498dfec5c81908b76d723b30dc2f0 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494b8098481908097228db8ad0262 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.