Triple
T3471157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durham, England |
E73260
|
entity |
| Predicate | distanceToNewcastleUponTyne_km |
P19337
|
FINISHED |
| Object | about 23 |
—
|
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 23 | Statement: [Durham, England, distanceToNewcastleUponTyne_km, about 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNewcastleUponTyne_km Context triple: [Durham, England, distanceToNewcastleUponTyne_km, about 23]
-
A.
distanceFromNewcastle
chosen
Indicates the spatial distance between a given entity or location and the city of Newcastle.
-
B.
distanceFromDurhamCity
Indicates the measured distance between an entity’s location and the city of Durham.
-
C.
distanceFromAlnwick
Indicates the measured distance between a given entity and the location of Alnwick.
-
D.
distanceFromNorwich
Indicates the measured distance between a given place or object and the location of Norwich.
-
E.
distanceToManchester
Indicates the measured or calculated distance between a given entity’s location and the city of Manchester.
- 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_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. |
Created at: March 8, 2026, 3:17 p.m.