Triple
T14138895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manises |
E350369
|
entity |
| Predicate | hasTransport |
P1298
|
FINISHED |
| Object | Valencia Metro |
E1039823
|
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: Valencia Metro | Statement: [Manises, hasTransport, Valencia Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valencia Metro Context triple: [Manises, hasTransport, Valencia Metro]
-
A.
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.
-
B.
Valencia Metro
chosen
Valencia Metro is the rapid transit system serving the city of Valencia and its metropolitan area in Spain.
-
C.
Seville Metro
Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
-
D.
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.
-
E.
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.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6111a36081909beff35c88a56960 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf16079c819080a74cd8a6eb37a6 |
completed | May 7, 2026, 6:51 p.m. |
Created at: April 10, 2026, 12:40 a.m.