Triple
T5944446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hui |
E132243
|
entity |
| Predicate | majorOccupationHistorical |
P17109
|
FINISHED |
| Object | trade |
—
|
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: trade | Statement: [Hui, majorOccupationHistorical, trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorOccupationHistorical Context triple: [Hui, majorOccupationHistorical, trade]
-
A.
earliestMajorOccupation
Indicates the earliest significant occupation or professional role held by an entity in its life or career timeline.
-
B.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
C.
traditionalOccupations
chosen
Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
-
D.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
E.
earliestOccupation
Indicates that the associated occupation is the first or earliest known job or professional role held by the person in question.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.