Triple
T10958042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kegworth |
E258895
|
entity |
| Predicate | distanceToM1Junction24 |
P96836
|
FINISHED |
| Object | approximately 1 mile |
—
|
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 1 mile | Statement: [Kegworth, distanceToM1Junction24, approximately 1 mile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToM1Junction24 Context triple: [Kegworth, distanceToM1Junction24, approximately 1 mile]
-
A.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
B.
distance to Midtown Manhattan (miles)
Indicates the physical separation between a location and Midtown Manhattan, measured in miles.
-
C.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceFromWatfordJunction
Indicates the spatial distance between a given location and Watford Junction.
-
E.
approximateDistanceFromHighway1
Indicates the estimated distance between a location and Highway 1, rather than an exact measured value.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77126d9288190aa5daf2ba83d731d |
completed | April 9, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.