Triple

T26556227
Position Surface form Disambiguated ID Type / Status
Subject Dardagny town hall E666114 entity
Predicate governsTerritory P10006 FINISHED
Object Dardagny municipality
Dardagny municipality is a local administrative district in the canton of Geneva, Switzerland, encompassing the village of Dardagny and its surrounding rural area.
E1733490 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: Dardagny municipality | Statement: [Dardagny town hall, governsTerritory, Dardagny municipality]
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: Dardagny municipality
Triple: [Dardagny town hall, governsTerritory, Dardagny municipality]
Generated description
Dardagny municipality is a local administrative district in the canton of Geneva, Switzerland, encompassing the village of Dardagny and its surrounding rural 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_69ee9cf7e94481909f0d556b36e43572 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f614661bc08190bd533fbfac7da9fe completed May 2, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec17199c8190a2ab7808bac93e33 completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11ecab0ab08190847f4751971939ec completed May 23, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_6a11ed32b3648190b32aa4fd2aae2643 completed May 23, 2026, 6:08 p.m.
Created at: April 27, 2026, 1:50 a.m.