Triple

T23589599
Position Surface form Disambiguated ID Type / Status
Subject Norwegian scientific community E582438 entity
Predicate includesInstitution P3814 FINISHED
Object Chr. Michelsen Institute
Chr. Michelsen Institute is an independent Norwegian research institute known for its work on development studies, human rights, and peace and conflict research.
E1596893 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: Chr. Michelsen Institute | Statement: [Norwegian scientific community, includesInstitution, Chr. Michelsen Institute]
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: Chr. Michelsen Institute
Triple: [Norwegian scientific community, includesInstitution, Chr. Michelsen Institute]
Generated description
Chr. Michelsen Institute is an independent Norwegian research institute known for its work on development studies, human rights, and peace and conflict research.

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_69e248f9e0a08190814772847003b1ff completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b0336aec8190856aee4a8273c3e5 completed April 29, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f457bc0388190a6e38f321829c89a completed May 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a0f4732991c819090acd6744f1b5cd5 completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47edf76c819083722440930ae47c completed May 21, 2026, 5:59 p.m.
Created at: April 17, 2026, 6:41 p.m.