Triple
T31016534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 大熊町 |
E790338
|
entity |
| Predicate | primaryIndustryBefore2011 |
P129420
|
FINISHED |
| Object | 農業 |
—
|
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: 農業 | Statement: [大熊町, primaryIndustryBefore2011, 農業]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryIndustryBefore2011 Context triple: [大熊町, primaryIndustryBefore2011, 農業]
-
A.
formerEconomicActivity
Indicates that an entity previously engaged in a specified economic activity but no longer does so.
-
B.
formerKeyIndustry
chosen
Indicates that an entity was once a primary or strategically important industry for another entity but no longer holds that status.
-
C.
primarySectorActivity
Indicates the main industry or sector in which an entity primarily conducts its activities or operations.
-
D.
hasPrimarySectorEmployment
Indicates that an entity is employed in the primary economic sector (e.g., agriculture, mining, forestry, or related extractive activities).
-
E.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a035ead9ee0819099806d2670dc9c50 |
completed | May 12, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_6a035dc9210c8190a9044c6a53211520 |
completed | May 12, 2026, 5:05 p.m. |
Created at: April 29, 2026, 8:57 p.m.