Triple

T37253976
Position Surface form Disambiguated ID Type / Status
Subject Plaça de Catalunya metro station E924070 entity
Predicate servedByLine P1293 FINISHED
Object FGC line L7
FGC line L7 is a Barcelona commuter rail line operated by Ferrocarrils de la Generalitat de Catalunya that connects Plaça de Catalunya with the Tibidabo area.
E2221130 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: FGC line L7 | Statement: [Plaça de Catalunya metro station, servedByLine, FGC line L7]
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: FGC line L7
Triple: [Plaça de Catalunya metro station, servedByLine, FGC line L7]
Generated description
FGC line L7 is a Barcelona commuter rail line operated by Ferrocarrils de la Generalitat de Catalunya that connects Plaça de Catalunya with the Tibidabo area.

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_69f76eaabb4c819093b751b139dad551 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb3729c6e481909a375336128176f5 completed May 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a405128946481909a5f05234d9855d4 completed June 27, 2026, 10:39 p.m.
NEDg Description generation batch_6a40521885c881909f2c4341374d60c8 completed June 27, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a405398da808190adfbac41f3c05ed7 completed June 27, 2026, 10:50 p.m.
Created at: May 3, 2026, 4:15 p.m.