Triple
T1066176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penzance |
E23214
|
entity |
| Predicate | hasBoroughStatusHistory |
P5556
|
FINISHED |
| Object | former municipal borough |
—
|
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: former municipal borough | Statement: [Penzance, hasBoroughStatusHistory, former municipal borough]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoroughStatusHistory Context triple: [Penzance, hasBoroughStatusHistory, former municipal borough]
-
A.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
-
B.
hasMunicipalStatusChange
chosen
Indicates that an entity undergoes a change in its official municipal status (e.g., creation, upgrade, downgrade, merger, or dissolution as a municipality).
-
C.
hasHistoricCountyStatusSince
Indicates that an entity has held the legal or recognized status of a historic county starting from a specified point in time.
-
D.
hasNearbyBorough
Indicates that one borough is geographically close to or adjacent to another borough.
-
E.
passesThroughBorough
Indicates that something (such as a route, line, or path) traverses or goes through a particular borough.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b9e1047481909af1cf8df2a01fff |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b736f1e881909bace735b38c0ade |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.