Triple
T27453330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awaba railway station |
E692510
|
entity |
| Predicate | distanceFromNewcastle_km |
P19337
|
FINISHED |
| Object | approximately 24 |
—
|
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 24 | Statement: [Awaba railway station, distanceFromNewcastle_km, approximately 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNewcastle_km Context triple: [Awaba railway station, distanceFromNewcastle_km, approximately 24]
-
A.
distanceToNewcastle_km
Indicates the physical distance, measured in kilometers, between a given location and Newcastle.
-
B.
distanceFromNewcastle
chosen
Indicates the spatial distance between a given entity or location and the city of Newcastle.
-
C.
distanceFromNewcastleCBD_km
Indicates the physical distance, measured in kilometers, between an entity and the central business district (CBD) of Newcastle.
-
D.
distanceToSunderland_km
Indicates the physical distance, measured in kilometers, between a given place and Sunderland.
-
E.
distanceFromSunderland
Indicates the spatial distance between a given entity and the location of Sunderland.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 27, 2026, 12:48 p.m.