Triple

T3267421
Position Surface form Disambiguated ID Type / Status
Subject BESIX E68559 entity
Predicate operatesIn P82 FINISHED
Object Australia E876 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: Australia | Statement: [BESIX, operatesIn, Australia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Australia
Context triple: [BESIX, operatesIn, Australia]
  • A. Australia chosen
    Australia is a large island continent and sovereign country in the Southern Hemisphere, known for its unique wildlife, diverse landscapes, and major cities such as Sydney and Melbourne.
  • B. Tasmania
    Tasmania is an island state of Australia known for its rugged wilderness, unique wildlife, and relatively cool maritime climate.
  • C. AU
    AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
  • D. AU
    AU is the commonly used abbreviation for Anna University, a prominent public technical university based in Chennai, India.
  • E. AU
    Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafce46dc8190a157e4f5012baed5 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ece1d1c81909bacadecea679a7f completed March 12, 2026, 10 a.m.
Created at: March 8, 2026, 3:09 p.m.