Triple
T4226565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Móstoles |
E94472
|
entity |
| Predicate | transportConnection |
P1298
|
FINISHED |
| Object | Madrid Metro |
E26338
|
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: Madrid Metro | Statement: [Móstoles, transportConnection, Madrid Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madrid Metro Context triple: [Móstoles, transportConnection, Madrid Metro]
-
A.
Madrid Metro
chosen
Madrid Metro is the extensive rapid transit system serving Spain’s capital, known for its large network, frequent service, and role as a primary mode of urban transportation.
-
B.
Seville Metro
Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
-
C.
Madrid Metro Line 1
Madrid Metro Line 1 is one of the oldest and busiest lines of the Madrid Metro, running in a north–south direction and connecting key central stations across the city.
-
D.
Metro Ligero de Madrid
Metro Ligero de Madrid is a light rail system serving several suburban and peripheral areas of Madrid, complementing the city's main metro network.
-
E.
Barcelona Metro
Barcelona Metro is the rapid transit rail network serving the city of Barcelona and its metropolitan area, known for its extensive coverage and integration with other public transport modes.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e4ed34c819081d1479ce87cd78c |
completed | March 12, 2026, 11:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a85c79a881908cadc892dc30d8ef |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 12, 2026, 11:04 p.m.