Triple
T38188761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Manchester |
E1005393
|
entity |
| Predicate | hasRailTerminusInManchester |
P196383
|
FINISHED |
| Object | Manchester Piccadilly railway station |
—
|
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: Manchester Piccadilly railway station | Statement: [London–Manchester, hasRailTerminusInManchester, Manchester Piccadilly railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailTerminusInManchester Context triple: [London–Manchester, hasRailTerminusInManchester, Manchester Piccadilly railway station]
-
A.
primaryManchesterStation
Indicates that a given station is the main or principal railway station serving Manchester.
-
B.
hasLondonUndergroundStation
Indicates that a place or area contains at least one London Underground (Tube) station within its boundaries.
-
C.
hasTerminusInCentralLondon
Indicates that the route, service, or line ends at a terminal point located within Central London.
-
D.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
E.
adjacentStopOnSouthManchesterLine
Indicates that one stop is immediately next to another stop along the South Manchester transit line.
- 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe2f078c24819082ba396b56f02808 |
completed | May 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69fe228fe1988190baf3bb34897f3dbe |
completed | May 8, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69fe2f066ac48190882c327b7e69e53f |
completed | May 8, 2026, 6:44 p.m. |
Created at: May 3, 2026, 4:29 p.m.