Triple
T14726541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheltenham (UK Parliament constituency) |
E345958
|
entity |
| Predicate | townType |
P749
|
FINISHED |
| Object | Regency spa town |
—
|
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: Regency spa town | Statement: [Cheltenham (UK Parliament constituency), townType, Regency spa town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: townType Context triple: [Cheltenham (UK Parliament constituency), townType, Regency spa town]
-
A.
town
Indicates that a location is classified or functions as a town within a given geographic or administrative context.
-
B.
urbanAreaType
chosen
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
C.
cityOrTown
Indicates that the subject is classified as a city or a town.
-
D.
countyType
Indicates the classification or category of a county within an administrative or governmental system.
-
E.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26013c8819090512f8b4df9cc87 |
completed | April 14, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69de657e174481909da0437556334a04 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.