Triple
T6505918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waimate District |
E150006
|
entity |
| Predicate | hasPrimaryIndustrySector |
P13077
|
FINISHED |
| Object | primary production |
—
|
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: primary production | Statement: [Waimate District, hasPrimaryIndustrySector, primary production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryIndustrySector Context triple: [Waimate District, hasPrimaryIndustrySector, primary production]
-
A.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
B.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
C.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
D.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
E.
hasOccupationSector
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab714908190aa7c2fbf64078e15 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:43 p.m.