Triple
T25400711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London suburban rail network |
E636408
|
entity |
| Predicate | hasCentralTerminus |
P160862
|
FINISHED |
| Object | London Euston |
—
|
NE NERFINISHED |
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: London Euston | Statement: [London suburban rail network, hasCentralTerminus, London Euston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCentralTerminus Context triple: [London suburban rail network, hasCentralTerminus, London Euston]
-
A.
hasCentralTerminus
chosen
Indicates that one entity serves as the primary or central terminus (end point or hub) for another entity.
-
B.
hasCapitalTerminus
Indicates that a transportation route or line has its endpoint located in a capital city.
-
C.
hasSuburbanTerminus
Indicates that a transportation route or service ends at a terminus located in a suburban area.
-
D.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
E.
locatedAtTerminusOf
Indicates that one entity is situated at the end point or final terminus of another entity, such as a route, line, or path.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 21, 2026, 1:50 p.m.