Triple
T3318907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tewkesbury (UK Parliament constituency) |
E69745
|
entity |
| Predicate | regionLabel |
P1828
|
FINISHED |
| Object | Constituency in England |
—
|
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: Constituency in England | Statement: [Tewkesbury (UK Parliament constituency), regionLabel, Constituency in England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionLabel Context triple: [Tewkesbury (UK Parliament constituency), regionLabel, Constituency in England]
-
A.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
B.
regionNamedAfter
Indicates that a geographic region derives its name from a specific person, place, event, or other entity.
-
C.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
-
D.
regionType
chosen
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
E.
regionNumber
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1151f3c8190911af4edac701116 |
completed | March 8, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69ada42a19348190a3862ce02451f4aa |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.