Triple
T37847251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ynys Môn (UK Parliament constituency) |
E943936
|
entity |
| Predicate | regionallyAdjacentTo |
P109543
|
FINISHED |
| Object | Arfon (UK Parliament constituency) |
—
|
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: Arfon (UK Parliament constituency) | Statement: [Ynys Môn (UK Parliament constituency), regionallyAdjacentTo, Arfon (UK Parliament constituency)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionallyAdjacentTo Context triple: [Ynys Môn (UK Parliament constituency), regionallyAdjacentTo, Arfon (UK Parliament constituency)]
-
A.
geographicallyAdjacentTo
Indicates that two geographic entities share a common boundary or are directly next to each other in space.
-
B.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
C.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
D.
regionalNeighbor
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
E.
geographicNeighbors
chosen
Indicates that two geographic entities share a common boundary or are directly adjacent to each other in space.
- 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_69f76eed4d9c81908b1b71ba9e3b61fe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a007aa8d3a481908543f9b5d562a90c |
completed | May 10, 2026, 12:31 p.m. |
| PD | Predicate disambiguation | batch_6a007a44996481908688ccfdbc56511d |
completed | May 10, 2026, 12:29 p.m. |
Created at: May 3, 2026, 4:19 p.m.