Triple
T33246636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groningen gas extraction area |
E851118
|
entity |
| Predicate | governmentStakeholder |
P194168
|
FINISHED |
| Object | Dutch national government |
—
|
NE NERFINISHED |
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: Dutch national government | Statement: [Groningen gas extraction area, governmentStakeholder, Dutch national government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governmentStakeholder Context triple: [Groningen gas extraction area, governmentStakeholder, Dutch national government]
-
A.
governmentPartner
Indicates that one entity collaborates with or is formally partnered with a government or governmental body in some capacity.
-
B.
governmentRespondent
Indicates that the entity functions as a government body or authority serving as the respondent in a legal, administrative, or formal proceeding.
-
C.
governmentCategory
Indicates the type or classification of a government associated with an entity.
-
D.
holderGovernment
Indicates that a government entity serves as the official holder, custodian, or controlling authority over another entity.
-
E.
government3
chosen
Indicates a relationship where an entity functions as or is associated with a government or governing body in a given context.
- 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_69f34962386c81909ddc3bf9e18ddeb8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a008c77d4dc8190b342d7407eaf48fa |
completed | May 10, 2026, 1:47 p.m. |
| PD | Predicate disambiguation | batch_6a008c18531c8190bbe883b73e6d023f |
completed | May 10, 2026, 1:46 p.m. |
Created at: May 1, 2026, 1:31 a.m.