Triple
T375286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merionethshire |
E8358
|
entity |
| Predicate | hasPrincipalIndustry |
P13077
|
FINISHED |
| Object | sheep farming |
—
|
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: sheep farming | Statement: [Merionethshire, hasPrincipalIndustry, sheep farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrincipalIndustry Context triple: [Merionethshire, hasPrincipalIndustry, sheep farming]
-
A.
hasHistoricIndustry
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
B.
isPrincipalAdvisorTo
Indicates that one entity serves as the main or primary advisor to another entity, providing overarching guidance or counsel.
-
C.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
D.
isPrincipalAdvisorOn
Indicates that one entity serves as the main or lead advisor to another entity on a specific matter, project, or role.
-
E.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
- F. None of above. chosen
Provenance (4 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec1585648190943f1c698e9b2d81 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ebcb1b2c8190a68bb3bad600c227 |
completed | Feb. 28, 2026, 1:21 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.