Triple
T746024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London, Midland and Scottish Railway |
E15342
|
entity |
| Predicate | networkLength |
P18592
|
FINISHED |
| Object | over 6,000 route 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: over 6,000 route miles | Statement: [London, Midland and Scottish Railway, networkLength, over 6,000 route miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkLength Context triple: [London, Midland and Scottish Railway, networkLength, over 6,000 route miles]
-
A.
roadSystemLength
Indicates the total length or extent of a road network associated with an entity.
-
B.
trailSystemLength
Indicates the total measured length of a trail system associated with an entity.
-
C.
branchCount
Indicates the number of branches associated with a given entity or structure.
-
D.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
-
E.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62ca1d081908e3191411f86498d |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ff10608190bfd60b4a1cb38f7d |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.