Triple
T37903929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Faroe Islands |
E945493
|
entity |
| Predicate | hasPrimaryIndustryInSetting |
P13077
|
FINISHED |
| Object | cod 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: cod fishing | Statement: [Spanish Faroe Islands, hasPrimaryIndustryInSetting, cod fishing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryIndustryInSetting Context triple: [Spanish Faroe Islands, hasPrimaryIndustryInSetting, cod fishing]
-
A.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
B.
hasSettingInIndustry
Indicates that something (such as a work, event, or scenario) takes place within or is situated in a particular industry context.
-
C.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
D.
hasPrimarySectorEmployment
Indicates that an entity is employed in the primary economic sector (e.g., agriculture, mining, forestry, or related extractive activities).
-
E.
isPrimarilyIndustrial
Indicates that the main or dominant use, function, or character of an entity is industrial in nature.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.