Triple
T17965997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Road |
E449206
|
entity |
| Predicate | hasNearbyTransport |
P1288
|
FINISHED |
| Object | Angel 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: Angel station | Statement: [City Road, hasNearbyTransport, Angel station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angel station Context triple: [City Road, hasNearbyTransport, Angel station]
-
A.
Angel station
chosen
Angel station is a London Underground station in Islington, known for serving the Northern line and its notably long escalators.
-
B.
Joanic station
Joanic station is an underground Barcelona Metro stop in the Gràcia district, serving passengers on the city’s Line 4.
-
C.
Central Station
Central Station is a key elevated stop on Jacksonville’s automated Skyway people mover system in downtown Jacksonville, Florida.
-
D.
Central Station
Central Station is a 1998 Brazilian drama film by Walter Salles that follows the emotional journey of a retired schoolteacher and a young boy traveling across Brazil in search of his father.
-
E.
Central Station
Central Station was the original name of Lisbon’s historic Rossio railway station, a key 19th-century rail hub known for its distinctive Neo-Manueline architecture.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1380960819089a3c0dd7cd57e5e |
completed | April 19, 2026, 10:40 a.m. |
Created at: April 10, 2026, 10:22 a.m.