Triple
T33617429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BFF |
E861156
|
entity |
| Predicate | hasLondonUndergroundCode |
P135757
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [BFF, hasLondonUndergroundCode, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLondonUndergroundCode Context triple: [BFF, hasLondonUndergroundCode, false]
-
A.
hasLondonUndergroundStation
Indicates that a place or area contains at least one London Underground (Tube) station within its boundaries.
-
B.
servedByOvergroundLine
Indicates that a location or facility is connected to and receives service from an Overground railway line.
-
C.
hasSubwayCode
chosen
Indicates that an entity is associated with a specific subway system code used to identify it within that transit network.
-
D.
hasLondonOvergroundPlatforms
Indicates that the subject has platforms specifically served by the London Overground rail network.
-
E.
enteredLondonUnderground
Indicates that an entity has gone into or begun using the London Underground transit system.
- 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_69f34980fabc81909819228729a9ca84 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: May 1, 2026, 1:41 a.m.