Triple
T8597715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loch Einich |
E203592
|
entity |
| Predicate | hasNearbyCorrie |
P83775
|
FINISHED |
| Object | Coire Dhondail |
—
|
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: Coire Dhondail | Statement: [Loch Einich, hasNearbyCorrie, Coire Dhondail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCorrie Context triple: [Loch Einich, hasNearbyCorrie, Coire Dhondail]
-
A.
hasNearbyCommon
Indicates that two entities share at least one common element, feature, or connection that is located within a specified nearby distance or vicinity.
-
B.
hasNearbyTrail
Indicates that one entity is located close to or within a short distance of a trail.
-
C.
hasNotableNearbyEntity
Indicates that one entity has another significant or noteworthy entity located in its close physical or contextual proximity.
-
D.
hasIslandNearby
Indicates that one location is situated close to an island in geographic space.
-
E.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
- F. None of above. chosen
Provenance (4 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46cacbe88190b95beeedc9f480b0 |
completed | March 31, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cc454504448190aaad2af8b17357cd |
completed | March 31, 2026, 10:05 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:24 p.m.