Triple

T11048023
Position Surface form Disambiguated ID Type / Status
Subject First Age E261178 entity
Predicate featuresCharacter P626 FINISHED
Object Niënor E675420 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: Niënor | Statement: [First Age, featuresCharacter, Niënor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niënor
Context triple: [First Age, featuresCharacter, Niënor]
  • A. Niënor Níniel chosen
    Niënor Níniel is a tragic figure from J.R.R. Tolkien’s legendarium, the daughter of Húrin and Morwen whose life is marked by amnesia, an unwitting incestuous marriage to her brother Túrin, and a despairing death under the shadow of Morgoth’s curse.
  • B. Nelion
    Nelion is one of the main twin summits of Mount Kenya, renowned among climbers for its challenging rock routes and high-altitude alpine terrain.
  • C. Neleus
    Neleus is a figure in Greek mythology, a son of Poseidon who became king of Pylos and fathered the heroic lineage that included Nestor.
  • D. Erigon
    Erigon is a high-performance, modular Ethereum execution client focused on efficient resource usage and fast synchronization.
  • E. Naberius
    Naberius is the main demonic antagonist in the film "I, Frankenstein," depicted as a powerful prince of demons seeking to harness reanimation technology for his own dark purposes.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798315b988190bc565581b2664009 completed April 9, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3aa06bae08190a0db615a258ded29 completed April 18, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:26 p.m.