Triple
T10574719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Barcelona Metro) |
E249578
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Navas station
Navas station is a Barcelona Metro stop in the Sant Andreu district, serving local commuters on the city's Line 1 network.
|
E878247
|
NE FINISHED |
How this triple was built (4 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: Navas station | Statement: [Line 1 (Barcelona Metro), hasStation, Navas station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Navas station Context triple: [Line 1 (Barcelona Metro), hasStation, Navas station]
-
A.
Medrano station
Medrano station is a stop on Buenos Aires’ Line B underground, serving the Almagro neighborhood near Avenida Medrano.
-
B.
Francisco Goitia station
Francisco Goitia station is a stop on the Xochimilco Light Rail system in Mexico City, serving local commuters in the southern part of the city.
-
C.
San Javier station
San Javier station is a major western terminus and transfer hub of the Medellín Metro system in Medellín, Colombia.
-
D.
Pedrero station
Pedrero station is a Santiago Metro stop in Chile located near the Estadio Monumental, serving passengers on the city’s Line 5.
-
E.
Martínez Nadal station
Martínez Nadal station is a rapid transit stop on the Tren Urbano system serving the San Juan metropolitan area in Puerto Rico.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Navas station Triple: [Line 1 (Barcelona Metro), hasStation, Navas station]
Generated description
Navas station is a Barcelona Metro stop in the Sant Andreu district, serving local commuters on the city's Line 1 network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Navas station Target entity description: Navas station is a Barcelona Metro stop in the Sant Andreu district, serving local commuters on the city's Line 1 network.
-
A.
Medrano station
Medrano station is a stop on Buenos Aires’ Line B underground, serving the Almagro neighborhood near Avenida Medrano.
-
B.
Francisco Goitia station
Francisco Goitia station is a stop on the Xochimilco Light Rail system in Mexico City, serving local commuters in the southern part of the city.
-
C.
San Javier station
San Javier station is a major western terminus and transfer hub of the Medellín Metro system in Medellín, Colombia.
-
D.
Pedrero station
Pedrero station is a Santiago Metro stop in Chile located near the Estadio Monumental, serving passengers on the city’s Line 5.
-
E.
Martínez Nadal station
Martínez Nadal station is a rapid transit stop on the Tren Urbano system serving the San Juan metropolitan area in Puerto Rico.
- F. None of above. chosen
Provenance (5 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98838c9b88190b12d8873695e219e |
completed | April 10, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69d98a945ecc8190b5aae7511a537650 |
completed | April 10, 2026, 11:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98b187c808190b785a46bb88d48fc |
completed | April 10, 2026, 11:43 p.m. |
Created at: April 6, 2026, 12:38 p.m.