Triple
T2476183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euston Underground station |
E55093
|
entity |
| Predicate | openedOnVictoriaLine |
P39712
|
FINISHED |
| Object | 1968 |
—
|
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: 1968 | Statement: [Euston Underground station, openedOnVictoriaLine, 1968]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedOnVictoriaLine Context triple: [Euston Underground station, openedOnVictoriaLine, 1968]
-
A.
openedAsRedLineStation
Indicates that a station began operation specifically as part of the Red Line when it first opened.
-
B.
openedAsSubway
Indicates that a transportation facility or line originally began operation specifically as a subway service.
-
C.
openedAsMBTAStation
Indicates that an entity began operation specifically as an MBTA station at a particular time.
-
D.
railwayLineOpened
Indicates that a railway line began official operation or service on a specified date.
-
E.
openedAsRailStop
Indicates that an entity began operation or was first established specifically as a railway stop.
- 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_69ab49e279e88190ab10d7248aea9d11 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1e45380819094b3f32a278bd457 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.