Triple
T26320583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balmullo |
E662096
|
entity |
| Predicate | distanceToDundee_km |
P5888
|
FINISHED |
| Object | approximately 16 |
—
|
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 16 | Statement: [Balmullo, distanceToDundee_km, approximately 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDundee_km Context triple: [Balmullo, distanceToDundee_km, approximately 16]
-
A.
distanceToDundee
chosen
Indicates the measured spatial distance between a given entity and the location of Dundee.
-
B.
distanceToEdinburgh_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Edinburgh.
-
C.
distanceFromGlasgow
Indicates the spatial distance separating a given entity or location from Glasgow.
-
D.
distanceFromEdinburghApprox
Indicates that an entity is located at an approximate distance from Edinburgh, rather than an exact measured distance.
-
E.
distanceToOban
Indicates the measured or calculated distance between a given entity or location and the place named Oban.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fdf5d05cc481909ec9e1b1f0784279 |
completed | May 8, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69fdf0cdd6948190838864ab3120dfa6 |
completed | May 8, 2026, 2:18 p.m. |
Created at: April 26, 2026, 10:28 p.m.