Triple

T6768820
Position Surface form Disambiguated ID Type / Status
Subject ANUIES E154991 entity
Predicate abbreviation P43 FINISHED
Object ANUIES E154991 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: ANUIES | Statement: [ANUIES, abbreviation, ANUIES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ANUIES
Context triple: [ANUIES, abbreviation, ANUIES]
  • A. ANUIES chosen
    ANUIES is a national association that brings together Mexican higher education institutions to coordinate policies, promote academic development, and strengthen the country’s university system.
  • B. AANES
    AANES is a de facto self-governing political entity in northern and eastern Syria, often associated with Kurdish-led, multi-ethnic autonomous administration and its experiment in decentralized, democratic governance.
  • C. NUAN
    NUAN is the stock ticker symbol for Nuance Communications, a company known for its speech recognition and conversational AI technologies.
  • D. Anini
    Anini is a remote town in the Dibang Valley district of Arunachal Pradesh in northeastern India, known for its rugged Himalayan terrain and proximity to the Dibang River.
  • E. UNON
    UNON is the United Nations Office at Nairobi, a major UN headquarters in Africa that hosts and supports numerous UN agencies and programs.
  • 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d232d1f08190bc30c0f24f28c475 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712c150088190b7e827cb1e45f1df completed March 27, 2026, 11:29 p.m.
Created at: March 27, 2026, 2:12 p.m.