Triple
T6665548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarrington |
E151591
|
entity |
| Predicate | distanceToNewarkOnTrent |
P72326
|
FINISHED |
| Object | approximately 10 miles |
—
|
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 10 miles | Statement: [Scarrington, distanceToNewarkOnTrent, approximately 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNewarkOnTrent Context triple: [Scarrington, distanceToNewarkOnTrent, approximately 10 miles]
-
A.
distanceToStokeOnTrent
Indicates the measured distance between a given entity’s location and the location of Stoke-on-Trent.
-
B.
distanceFromNewcastle
Indicates the spatial distance between a given entity or location and the city of Newcastle.
-
C.
distanceToNewport
Indicates the measured or calculated distance between a given entity and the location named Newport.
-
D.
distanceToPoughkeepsie
Indicates the spatial distance between a given entity and the location of Poughkeepsie.
-
E.
distanceToNottingham
Indicates the measured or estimated distance between a given location or entity and the city of Nottingham.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6ce72809c8190be85f6e42ca1c8ea |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 2:02 p.m.