Triple
T38188781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Manchester |
E1005393
|
entity |
| Predicate | hasApproximateDistanceByRail |
P65643
|
FINISHED |
| Object | about 163 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: about 163 miles | Statement: [London–Manchester, hasApproximateDistanceByRail, about 163 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateDistanceByRail Context triple: [London–Manchester, hasApproximateDistanceByRail, about 163 miles]
-
A.
distanceToByRail
chosen
Indicates the distance between two locations when traveling via railway routes.
-
B.
distanceToRailhead
Indicates the measured distance between a location or object and the nearest railhead (rail transport access point).
-
C.
hasApproximateDrivingDistanceFrom
Indicates that one entity is located at an estimated or approximate driving distance from another entity, typically measured along road routes rather than as a precise or exact value.
-
D.
approximateRouteLength
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
-
E.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
- 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
Created at: May 3, 2026, 4:29 p.m.