Triple
T6661316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle Carretas |
E151482
|
entity |
| Predicate | hasNearbyTransport |
P1288
|
FINISHED |
| Object | Sol station |
E140902
|
NE 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: Sol station | Statement: [Calle Carretas, hasNearbyTransport, Sol station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sol station Context triple: [Calle Carretas, hasNearbyTransport, Sol station]
-
A.
Sol station
chosen
Sol station is a major central railway and metro hub in Madrid, Spain, serving as a key interchange point for Cercanías commuter trains and multiple urban transit lines beneath Puerta del Sol.
-
B.
Kaeson Station
Kaeson Station is a notable stop on Pyongyang’s metro system, known for its grand socialist-realist decor and proximity to the Arch of Triumph.
-
C.
Konsol Station
Konsol Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
D.
Savage station
Savage station is a commuter rail stop in Savage, Maryland, serving passengers on MARC's Camden Line between Washington, D.C., and Baltimore.
-
E.
Bethesda station
Bethesda station is an underground Washington Metro station in Bethesda, Maryland, serving the Red Line and the surrounding downtown commercial district.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0737cb08190ad455b48fd30eec8 |
completed | March 27, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef0a0c208190ac6a309bfb2e4e4b |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:02 p.m.