Triple
T23986606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenford |
E604956
|
entity |
| Predicate | hasLondonUndergroundStation |
P154142
|
FINISHED |
| Object | Greenford tube 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: Greenford tube station | Statement: [Greenford, hasLondonUndergroundStation, Greenford tube station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLondonUndergroundStation Context triple: [Greenford, hasLondonUndergroundStation, Greenford tube station]
-
A.
hasLondonOvergroundPlatforms
Indicates that the subject has platforms specifically served by the London Overground rail network.
-
B.
hasAdjacentStationOnElizabethLine
Indicates that one station is directly next to another station along the Elizabeth Line, with no other stations in between.
-
C.
servedByOvergroundLine
Indicates that a location or facility is connected to and receives service from an Overground railway line.
-
D.
isAdjacentStationOnPiccadillyLine
Indicates that two stations are directly next to each other as consecutive stops on the Piccadilly Line.
-
E.
hasNeighbouringStationOnNorthLondonLine
Indicates that one station is directly adjacent to another station along the North London 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2c1d4508190905a3eb2d98a248b |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 9:36 p.m.