Triple
T19820042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattersey |
E476164
|
entity |
| Predicate | civilParishOf |
P9019
|
FINISHED |
| Object | Mattersey |
—
|
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: Mattersey | Statement: [Mattersey, civilParishOf, Mattersey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mattersey Context triple: [Mattersey, civilParishOf, Mattersey]
-
A.
Mattersey
chosen
Mattersey is a small village and civil parish in Nottinghamshire, England, known for its rural setting and historic priory remains.
-
B.
Meservey
Meservey is a surname of English origin borne by various individuals, including the American actor Robert Preston.
-
C.
Mattituck
Mattituck is a small hamlet and wine-country community on the North Fork of Long Island in Suffolk County, New York.
-
D.
Montignez
Montignez is a small former municipality in the canton of Jura in northwestern Switzerland, near the French border.
-
E.
Loyalton
Loyalton is a small city in northeastern California that serves as the primary population center of rural Sierra County.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654fe0ff8819084bad251b76eff77 |
completed | April 20, 2026, 4:31 p.m. |
Created at: April 10, 2026, 1:50 p.m.