Triple
T9862436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bank Underground station |
E239747
|
entity |
| Predicate | hasDLRStationCode |
P1289
|
FINISHED |
| Object | BAN |
—
|
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: BAN | Statement: [Bank Underground station, hasDLRStationCode, BAN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDLRStationCode Context triple: [Bank Underground station, hasDLRStationCode, BAN]
-
A.
hasDLRInterchange
Indicates that there is an interchange connection between an entity and a Docklands Light Railway (DLR) service or station.
-
B.
hasStationCode
chosen
Indicates that an entity is associated with a specific station identification code.
-
C.
hasStationCodeSystem
Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
-
D.
isPassengerStationCode
Indicates that a given code is officially assigned to identify a particular passenger station.
-
E.
hasStationAtAirport
Indicates that an organization or service operates a station or facility located at a specific airport.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3b7b81c81909a84f6ced829f394 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:35 p.m.