Triple
T2280441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcelona Metro |
E51267
|
entity |
| Predicate | integratedWith |
P2830
|
FINISHED |
| Object | Trambaix |
E51268
|
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: Trambaix | Statement: [Barcelona Metro, integratedWith, Trambaix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trambaix Context triple: [Barcelona Metro, integratedWith, Trambaix]
-
A.
Trambaix
chosen
Trambaix is a modern tram network serving the metropolitan area of Barcelona, particularly its western suburbs and nearby municipalities.
-
B.
Trambesòs
Trambesòs is a modern tram network serving Barcelona’s northeastern metropolitan area, connecting the city with nearby coastal and suburban districts.
-
C.
Blanquivermells
Blanquivermells is the popular nickname of Girona FC, referring to the club’s traditional white-and-red team colors.
-
D.
Calaisienne
Calaisienne is the French term for a female inhabitant or native of the port city of Calais in northern France.
-
E.
Sauter
Sauter is a surname of German origin, often associated with individuals in fields such as music, engineering, and business.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21ac3d48190abef254e1c3f45e8 |
completed | March 7, 2026, 6:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71e48fb081908498f826167020a2 |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.