Triple
T24647567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glencairn |
E610156
|
entity |
| Predicate | hasMunicipalityName |
P116572
|
FINISHED |
| Object | Essa |
—
|
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: Essa | Statement: [Glencairn, hasMunicipalityName, Essa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalityName Context triple: [Glencairn, hasMunicipalityName, Essa]
-
A.
hasMunicipalUnitName
Indicates that an entity is associated with the specific name of a municipal unit (such as a town, district, or local administrative division).
-
B.
hasNameInMunicipality
Indicates that an entity is known by a particular name within the context or jurisdiction of a specific municipality.
-
C.
municipalityName
chosen
Indicates the official name assigned to a municipality.
-
D.
isMunicipalHomeOf
Indicates that a municipality serves as the official home base or hosting location for a particular entity or organization.
-
E.
hasMetropolitanAreaName
Indicates that an entity is associated with a metropolitan area identified by a specific name.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:33 a.m.