Triple

T24484073
Position Surface form Disambiguated ID Type / Status
Subject municipal council of Haynrode E617457 entity
Predicate governs P760 FINISHED
Object municipality of Haynrode
The municipality of Haynrode is a local administrative community in Germany responsible for providing public services and local governance to its residents.
E1636926 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: municipality of Haynrode | Statement: [municipal council of Haynrode, governs, municipality of Haynrode]
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: municipality of Haynrode
Triple: [municipal council of Haynrode, governs, municipality of Haynrode]
Generated description
The municipality of Haynrode is a local administrative community in Germany responsible for providing public services and local governance to its residents.

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_69e2d7f3ae788190b683394db15f220e completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2a6d97e5481908acf33263a92e056 completed April 30, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee7a8cb88190b893b7ac247dc6af completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0fef3ca1e4819093c95f497eb37e82 completed May 22, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0feff2170481909764b1d8ab9f0afc completed May 22, 2026, 5:56 a.m.
Created at: April 18, 2026, 2:21 a.m.