Triple
T20443514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolton railway station |
E501454
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | BON |
—
|
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: BON | Statement: [Bolton railway station, hasStationCode, BON]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BON Context triple: [Bolton railway station, hasStationCode, BON]
-
A.
BON
BON is the IATA airport code for Flamingo International Airport, the main air gateway to the Caribbean island of Bonaire.
-
B.
BON
chosen
BON is the National Rail station code for Bolton railway station in Greater Manchester, England.
-
C.
BoN
BoN is the central bank of Namibia, responsible for issuing the national currency and overseeing the country’s monetary and financial stability.
-
D.
Bonne
Bonne of Berry was a 14th-century French noblewoman of the House of Valois, daughter of John II of France and a politically significant figure through her dynastic marriages.
-
E.
Bonne
Bonne is a small alpine village in the Valgrisenche valley of Italy’s Aosta Valley region, known for its mountainous surroundings and traditional rural character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfa7dd08190883a37e3480b152c |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.