Triple

T126500
Position Surface form Disambiguated ID Type / Status
Subject Royal Spanish Academy E2561 entity
Predicate hasChair P377 FINISHED
Object Chair E E13991 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: Chair E | Statement: [Royal Spanish Academy, hasChair, Chair E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chair E
Context triple: [Royal Spanish Academy, hasChair, Chair E]
  • A. Chair A chosen
    Chair A is one of the numbered academic seats of the Royal Spanish Academy, traditionally assigned to a distinguished scholar of the Spanish language.
  • B. First Chamber
    The First Chamber is the upper house of the Dutch parliament, responsible for reviewing and approving legislation passed by the lower house.
  • C. Earl
    An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
  • D. Porter
    Porter is a transit station in Cambridge, Massachusetts that serves both MBTA commuter rail and Red Line subway services.
  • E. Second Chamber
    The Second Chamber is the lower house of the Dutch parliament, responsible for initiating and scrutinizing legislation and overseeing the government.
  • 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_69a251b54ea88190b18281669f59b4c0 completed Feb. 28, 2026, 2:23 a.m.
NER Named-entity recognition batch_69a25761e9248190a7205bfc36cb5c45 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2b01814e88190a21f98527b8f9420 completed Feb. 28, 2026, 9:06 a.m.
Created at: Feb. 28, 2026, 2:27 a.m.