Triple
T22513595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanesborough |
E556583
|
entity |
| Predicate | hasNearbyCountyBoundary |
P131063
|
FINISHED |
| Object | County Longford–County Roscommon boundary |
—
|
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: County Longford–County Roscommon boundary | Statement: [Lanesborough, hasNearbyCountyBoundary, County Longford–County Roscommon boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCountyBoundary Context triple: [Lanesborough, hasNearbyCountyBoundary, County Longford–County Roscommon boundary]
-
A.
hasNearbyCountyBorder
Indicates that the borders of two counties are geographically close to each other, though not necessarily directly adjacent.
-
B.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
C.
hasNearbyBoundary
chosen
Indicates that one entity’s boundary lies close to, but does not necessarily touch or coincide with, the boundary of another entity.
-
D.
hasNearbyBorough
Indicates that one borough is geographically close to or adjacent to another borough.
-
E.
hasNearbyPrecinct
Indicates that one location has a police precinct or similar administrative station situated close to it in geographic proximity.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d62bea48190aaf34aa93bb3f67b |
completed | April 29, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.