Triple
T3471159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durham, England |
E73260
|
entity |
| Predicate | distanceToSunderland_km |
P49161
|
FINISHED |
| Object | about 20 |
—
|
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: about 20 | Statement: [Durham, England, distanceToSunderland_km, about 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSunderland_km Context triple: [Durham, England, distanceToSunderland_km, about 20]
-
A.
distanceFromLiverpoolCityCentre
Indicates the spatial distance between a given location and the center of Liverpool city.
-
B.
distanceFromNewcastle
Indicates the spatial distance between a given entity or location and the city of Newcastle.
-
C.
distanceToManchester
Indicates the measured or calculated distance between a given entity’s location and the city of Manchester.
-
D.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
E.
distanceFromLiverpoolLimeStreet
Indicates the spatial distance between a given location and Liverpool Lime Street station.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3af0cc81909e575828caeaeae0 |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:17 p.m.