Triple

T28339305
Position Surface form Disambiguated ID Type / Status
Subject C-55 road E717765 entity
Predicate connectsToRoad P22217 FINISHED
Object C-58 motorway
The C-58 motorway is a major highway in Catalonia, Spain, that links Barcelona with its northern metropolitan and inland areas, including Sabadell and Terrassa.
 E2295288 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: C-58 motorway | Statement: [C-55 road, connectsToRoad, C-58 motorway]
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: C-58 motorway
Triple: [C-55 road, connectsToRoad, C-58 motorway]
Generated description
The C-58 motorway is a major highway in Catalonia, Spain, that links Barcelona with its northern metropolitan and inland areas, including Sabadell and Terrassa.

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_69eff6eb30388190b898b96c4be6f49d completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bd73f6c8190bb7b109eccbf44b7 completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d33d1afe8819085e8f744e2b7a526 completed Aug. 13, 2026, 3:02 a.m.
NEDg Description generation batch_6a7d3641e320819086da2a30c0d68c55 completed Aug. 13, 2026, 3:13 a.m.
NED2 Entity disambiguation (via description) batch_6a7d36b1df108190b44567ff82453911 completed Aug. 13, 2026, 3:14 a.m.
Created at: April 28, 2026, 12:38 a.m.