Triple
T30070574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirk o’ Field, Edinburgh |
E764170
|
entity |
| Predicate | nearbyModernLandmark |
P61270
|
FINISHED |
| Object | University of Edinburgh central area |
—
|
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: University of Edinburgh central area | Statement: [Kirk o’ Field, Edinburgh, nearbyModernLandmark, University of Edinburgh central area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyModernLandmark Context triple: [Kirk o’ Field, Edinburgh, nearbyModernLandmark, University of Edinburgh central area]
-
A.
typicalNearbyLandmarks
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
B.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
C.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
-
D.
infrastructureNearby
Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
-
E.
nearbyHeritageDestinations
Indicates that one or more heritage destinations are located close to a given reference point or entity in geographic 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: April 29, 2026, 7 p.m.