Triple

T35935745
Position Surface form Disambiguated ID Type / Status
Subject Lichtenau (Alluitsoq) mission area E1039299 entity
Predicate namedAfter P63 FINISHED
Object Lichtenau
Lichtenau is a former Moravian mission settlement in southern Greenland, historically known for its role in Christian missionary activity among the Inuit.
E2164392 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: Lichtenau | Statement: [Lichtenau (Alluitsoq) mission area, namedAfter, Lichtenau]
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: Lichtenau
Triple: [Lichtenau (Alluitsoq) mission area, namedAfter, Lichtenau]
Generated description
Lichtenau is a former Moravian mission settlement in southern Greenland, historically known for its role in Christian missionary activity among the Inuit.

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_69f76e23e4688190a5369138755138bf completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aba98d30819089ba0fa9a016eca5 completed May 3, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfcc2d888190a732219a891cf907 completed June 22, 2026, 4:53 a.m.
NEDg Description generation batch_6a38c088eb848190a35f4cff5101fea5 completed June 22, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a38c11341d48190a70b63b26023add0 completed June 22, 2026, 4:58 a.m.
Created at: May 3, 2026, 4:07 p.m.