Triple
T17571686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckinghamshire and Hertfordshire |
E427954
|
entity |
| Predicate | areNeighboringCounties |
P6346
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Buckinghamshire and Hertfordshire, areNeighboringCounties, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areNeighboringCounties Context triple: [Buckinghamshire and Hertfordshire, areNeighboringCounties, true]
-
A.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
B.
hasNearbyCountyBorder
Indicates that the borders of two counties are geographically close to each other, though not necessarily directly adjacent.
-
C.
adjacentToCounty
chosen
Indicates that one county directly borders or touches another county geographically.
-
D.
isCornerCountyOf
Indicates that a county lies at or near the corner where two or more larger administrative regions (such as states or districts) meet.
-
E.
sharesCountyWith
Indicates that two entities are located within the same county jurisdiction.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45930b0748190b55b95c523c47460 |
completed | April 19, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.