Triple
T10646506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transports Metropolitans de Barcelona |
E250847
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
TMB
TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
|
E878171
|
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: TMB | Statement: [Transports Metropolitans de Barcelona, shortName, TMB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TMB Context triple: [Transports Metropolitans de Barcelona, shortName, TMB]
-
A.
TMB
TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
-
B.
TMB 2000 series
The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
-
C.
TMB 7000 series
The TMB 7000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
-
D.
TMB 5000 series
The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
-
E.
TMB 3000 series
The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
- 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: TMB Triple: [Transports Metropolitans de Barcelona, shortName, TMB]
Generated description
TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TMB Target entity description: TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
-
A.
TMB
TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
-
B.
TMB 2000 series
The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
-
C.
TMB 7000 series
The TMB 7000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
-
D.
TMB 5000 series
The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
-
E.
TMB 3000 series
The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe1cd6081909df9e4dc0fda1f0b |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a580d388190aea5edadd4afc0d1 |
completed | April 10, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69d97cc20448819094d650b9c1067dca |
completed | April 10, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d97e0cda0c8190af5013b971b2ad3c |
completed | April 10, 2026, 10:47 p.m. |
Created at: April 8, 2026, 9:05 p.m.