Triple
T32579949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabinet committees |
E832753
|
entity |
| Predicate | existsInCountry |
P174617
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [Cabinet committees, existsInCountry, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: existsInCountry Context triple: [Cabinet committees, existsInCountry, United Kingdom]
-
A.
existsInConstituentCountry
Indicates that one entity is located within or is present in a country that is a constituent part of a larger sovereign state.
-
B.
isSetInCountry
Indicates that something (such as an event, story, or scene) takes place within the geographical or political boundaries of a specified country.
-
C.
meetsInCountry
Indicates that two or more entities have an in-person meeting that takes place within the specified country.
-
D.
locatedInCurrentCountry
Indicates that an entity is situated within the geographic boundaries of the country in which it is presently found.
-
E.
includesPresentCountry
Indicates that an entity (such as a region, organization, or grouping) currently contains or encompasses a specified country within its present composition or membership.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c668b2ac8190931e5989cdcb9750 |
completed | May 3, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c2df27ec8190912ec8eb488836d0 |
completed | May 3, 2026, 3:37 a.m. |
Created at: May 1, 2026, 1:04 a.m.