Triple
T14096434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harsusi language |
E339263
|
entity |
| Predicate | mainSpeakerOccupation |
P102393
|
FINISHED |
| Object | pastoralists |
—
|
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: pastoralists | Statement: [Harsusi language, mainSpeakerOccupation, pastoralists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainSpeakerOccupation Context triple: [Harsusi language, mainSpeakerOccupation, pastoralists]
-
A.
presenterOccupation
Indicates that an entity serves in a specific professional role or job as a presenter.
-
B.
primarySpeakersOccupation
chosen
Indicates the main or most common occupation held by the speakers of a given language.
-
C.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
D.
narratorOccupation
Indicates that the specified occupation is the job or professional role held by the narrator.
-
E.
proposerOccupation
Indicates the occupation or professional role held by the entity acting as the proposer in a given context.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb926288190a7f0f50d1d585d76 |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.