Triple

T24304274
Position Surface form Disambiguated ID Type / Status
Subject Plantage Muidergracht E612489 entity
Predicate adjacentTo P224 FINISHED
Object Plantage Muidergracht canal
Plantage Muidergracht canal is a historic waterway in Amsterdam’s Plantage neighborhood, lined with 19th-century buildings and cultural institutions.
E1657167 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: Plantage Muidergracht canal | Statement: [Plantage Muidergracht, adjacentTo, Plantage Muidergracht canal]
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: Plantage Muidergracht canal
Triple: [Plantage Muidergracht, adjacentTo, Plantage Muidergracht canal]
Generated description
Plantage Muidergracht canal is a historic waterway in Amsterdam’s Plantage neighborhood, lined with 19th-century buildings and cultural institutions.

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_69e2d7d91bb48190bc5377d17a85fb21 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29224c7cc8190bd1a32318198326c completed April 29, 2026, 11:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1032dd6864819089e928f1b5d4438b completed May 22, 2026, 10:41 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034cf890881908bd25523cdb83586 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 1:29 a.m.