Triple
T9140874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marton parish |
E219322
|
entity |
| Predicate | hasCivilFunction |
P17162
|
FINISHED |
| Object | civil parish |
—
|
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: civil parish | Statement: [Marton parish, hasCivilFunction, civil parish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilFunction Context triple: [Marton parish, hasCivilFunction, civil parish]
-
A.
hasCivicFunction
chosen
Indicates that an entity performs, is responsible for, or is associated with an official public or civic role, duty, or service.
-
B.
hasCivilArea
Indicates that an administrative or political entity encompasses or is associated with a specific civil (local administrative) area.
-
C.
hadJudicialFunction
Indicates that an entity exercised or was assigned an official judicial role, authority, or responsibility in relation to another entity or context.
-
D.
hasCivilSection
Indicates that one legal document, case, or record includes or is associated with a specific civil law section or provision.
-
E.
hasLegalFunction
Indicates that an entity performs, fulfills, or is assigned a specific legal role, duty, or function within a legal or regulatory 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8f2537881908956a9b0516e2d49 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.