Triple

T32759853
Position Surface form Disambiguated ID Type / Status
Subject Spijkenisse E837725 entity
Predicate servedByMetroLine P6301 FINISHED
Object Rotterdam Metro line C
Rotterdam Metro line C is a rapid transit line in the Rotterdam Metro network that runs between De Terp in Capelle aan den IJssel and De Akkers in Spijkenisse, serving multiple suburbs and city districts along the way.
E351568 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: Rotterdam Metro line C | Statement: [Spijkenisse, servedByMetroLine, Rotterdam Metro line C]
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: Rotterdam Metro line C
Triple: [Spijkenisse, servedByMetroLine, Rotterdam Metro line C]
Generated description
Rotterdam Metro line C is a rapid transit line in the Rotterdam Metro network that runs between De Terp in Capelle aan den IJssel and De Akkers in Spijkenisse, serving multiple suburbs and city districts along the way.

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_69f34939857c8190aa9970c51feec1eb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cce3632881908c9d2274a358c712 completed May 3, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b15e634081908df87573eba22575 completed June 19, 2026, 3:02 a.m.
NEDg Description generation batch_6a34b1f2f6d4819082e910d0685eb95e completed June 19, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a34b279c8688190b257df5ca22d7dd9 completed June 19, 2026, 3:07 a.m.
Created at: May 1, 2026, 1:13 a.m.