Triple
T10081893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spean Bridge |
E213920
|
entity |
| Predicate | distanceToCommandoMemorial |
P53174
|
FINISHED |
| Object | approximately 1.5 kilometres |
—
|
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: approximately 1.5 kilometres | Statement: [Spean Bridge, distanceToCommandoMemorial, approximately 1.5 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCommandoMemorial Context triple: [Spean Bridge, distanceToCommandoMemorial, approximately 1.5 kilometres]
-
A.
distanceFromFord’sTheatre
Indicates the spatial distance between an entity and Ford’s Theatre.
-
B.
memorialLocatedAt
Indicates that a memorial is situated or found at a specific location.
-
C.
distanceToWashingtonMonument
Indicates the physical distance between a given entity’s location and the Washington Monument.
-
D.
proximityToLandmark
chosen
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
-
E.
distanceFromGeorgeTown
Indicates the measured spatial distance between a given location and George Town.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd03482d481908b03d35dc2d16395 |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.