Triple

T23938046
Position Surface form Disambiguated ID Type / Status
Subject Aker ASA E602695 entity
Predicate subsidiary P258 FINISHED
Object Aker BioMarine ASA
Aker BioMarine ASA is a Norwegian biotechnology and fishing company specializing in sustainable krill harvesting and the production of krill-based ingredients for nutraceutical, aquaculture, and pet food markets.
E602695 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: Aker BioMarine ASA | Statement: [Aker ASA, subsidiary, Aker BioMarine ASA]
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: Aker BioMarine ASA
Triple: [Aker ASA, subsidiary, Aker BioMarine ASA]
Generated description
Aker BioMarine ASA is a Norwegian biotechnology and fishing company specializing in sustainable krill harvesting and the production of krill-based ingredients for nutraceutical, aquaculture, and pet food markets.

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_69e2953cf6e081909b8e25a10a52dddc completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1cfa1336c8190ac307a1b9497ba0b completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e6f1e288190bdd49b84f55eb47f completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7f6d3d0c8190a408c4dee4ac1f93 completed May 21, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f8038a6d08190a2f763934018c64e completed May 21, 2026, 9:59 p.m.
Created at: April 17, 2026, 9:07 p.m.