Triple
T20983014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 3 (Seville Metro) |
E516812
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Metro de Sevilla |
—
|
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: Metro de Sevilla | Statement: [Line 3 (Seville Metro), operator, Metro de Sevilla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metro de Sevilla Context triple: [Line 3 (Seville Metro), operator, Metro de Sevilla]
-
A.
Seville Metro
chosen
Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
-
B.
Seville commuter rail
Seville commuter rail is a regional rail network serving the metropolitan area of Seville, Spain, connecting the city with its surrounding suburbs and towns.
-
C.
Madrid Metro
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.
-
D.
Valencia Metro
Valencia Metro is the rapid transit system serving the city of Valencia and its metropolitan area in Spain.
-
E.
Valencia Metro
Valencia Metro is the rapid transit system serving the city of Valencia in Venezuela, providing urban rail transportation across key areas of the metropolitan region.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbe03244819097630333e70c4e88 |
completed | April 21, 2026, 4:24 a.m. |
Created at: April 16, 2026, 1:48 p.m.