Triple

T22801558
Position Surface form Disambiguated ID Type / Status
Subject Oost Gelre E564406 entity
Predicate contains P35 FINISHED
Object Groenlo
Groenlo is a historic town in the Dutch province of Gelderland, known for its well-preserved fortifications and role in the Eighty Years' War.
E2287693 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: Groenlo | Statement: [Oost Gelre, contains, Groenlo]
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: Groenlo
Triple: [Oost Gelre, contains, Groenlo]
Generated description
Groenlo is a historic town in the Dutch province of Gelderland, known for its well-preserved fortifications and role in the Eighty Years' War.

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_69e2458185f88190b0045227ee420411 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cdd87648190ba30f0b8f3ef7346 completed April 29, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5a0c4d2de481908487bdaa2fdcbd72 completed July 17, 2026, 11:04 a.m.
NEDg Description generation batch_6a5a0d2b49108190977dc434f63f20b3 completed July 17, 2026, 11:08 a.m.
NED2 Entity disambiguation (via description) batch_6a5a0e18fc7c8190b84670454596f9d7 completed July 17, 2026, 11:12 a.m.
Created at: April 17, 2026, 3:31 p.m.