Triple

T8397331
Position Surface form Disambiguated ID Type / Status
Subject Argishti I E198086 entity
Predicate predecessor P97 FINISHED
Object Menua E198085 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: Menua | Statement: [Argishti I, predecessor, Menua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Menua
Context triple: [Argishti I, predecessor, Menua]
  • A. Menua chosen
    Menua was a prominent king of the ancient kingdom of Urartu, known for expanding its territory and developing extensive irrigation and fortification projects.
  • B. Tarro
    Tarro is a suburban railway station in the Hunter Region of New South Wales, Australia, serving the local community on the Main Northern line.
  • C. Mandulis
    Mandulis is a Nubian sun god venerated in the region of Lower Nubia, particularly during the Greco-Roman period.
  • D. Meatu
    Meatu is a rural district and administrative settlement in northern Tanzania’s Simiyu Region, known for its agriculture and livestock-keeping communities.
  • E. Farino
    Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb818a8dc081908efd5d7f910322e7 completed March 31, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d2a17e481908c7eab4624903251 completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:04 p.m.