Triple
T35696657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berg municipality |
E1031459
|
entity |
| Predicate | hadMainIndustry |
P20603
|
FINISHED |
| Object | fishing |
—
|
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: fishing | Statement: [Berg municipality, hadMainIndustry, fishing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMainIndustry Context triple: [Berg municipality, hadMainIndustry, fishing]
-
A.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
B.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
C.
formerKeyIndustry
Indicates that an entity was once a primary or strategically important industry for another entity but no longer holds that status.
-
D.
hadStateOwnershipOfIndustry
Indicates that a governing authority or state entity possessed ownership and control over a particular industry.
-
E.
hadMajorCompany
Indicates that an entity previously owned, led, or was primarily associated with a major company.
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:05 p.m.