Triple

T13788890
Position Surface form Disambiguated ID Type / Status
Subject Herring Networks, Inc. E331338 entity
Predicate alternativeName P39 FINISHED
Object Herring Networks E331338 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: Herring Networks | Statement: [Herring Networks, Inc., alternativeName, Herring Networks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herring Networks
Context triple: [Herring Networks, Inc., alternativeName, Herring Networks]
  • A. Herring Networks, Inc. chosen
    Herring Networks, Inc. is a conservative-leaning American media company best known for operating the cable news channel One America News Network (OANN).
  • B. Aurora Network
    Aurora Network is a European university alliance focused on collaboration in research, education, and innovation among its member institutions.
  • C. Helionix
    Helionix is an advanced, integrated avionics system developed by Airbus Helicopters to enhance situational awareness, safety, and mission efficiency in modern rotorcraft.
  • D. Barracuda Networks
    Barracuda Networks is a cybersecurity and data protection company known for providing email security, network security, and backup solutions for businesses.
  • E. Nitelink
    Nitelink is Dublin’s late-night bus service network, providing after-hours public transport on key routes across the city and suburbs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de024af32c8190a9bd1278e09564ba completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b07f5cf48190b59827efb5918a95 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 10:11 p.m.