Triple

T29544593
Position Surface form Disambiguated ID Type / Status
Subject Mandø E749596 entity
Predicate hasBuilding P105 FINISHED
Object Mandø Church
Mandø Church is a small historic parish church serving the island community of Mandø in the Wadden Sea off the west coast of Denmark.
E1875795 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: Mandø Church | Statement: [Mandø, hasBuilding, Mandø Church]
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: Mandø Church
Triple: [Mandø, hasBuilding, Mandø Church]
Generated description
Mandø Church is a small historic parish church serving the island community of Mandø in the Wadden Sea off the west coast of Denmark.

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_69f0bd48691081908cecad39bac591e0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66cf1571c81909b868f644090d068 completed May 2, 2026, 9:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a266156aca88190bf08db38e23c3b66 completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a2665b107d48190af6ed8efb30d61d7 completed June 8, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_6a266a4b72048190966d23bf400a578f completed June 8, 2026, 7:07 a.m.
Created at: April 28, 2026, 5:06 p.m.