Triple

T9515286
Position Surface form Disambiguated ID Type / Status
Subject Summer Eights E229508 entity
Predicate relatedEvent P37 FINISHED
Object Torpids E229507 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: Torpids | Statement: [Summer Eights, relatedEvent, Torpids]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torpids
Context triple: [Summer Eights, relatedEvent, Torpids]
  • A. Torpids chosen
    Torpids is an annual bumps rowing competition held on the River Thames in Oxford, featuring college crews from the University of Oxford.
  • B. Torp
    Torp is a Norwegian surname most notably associated with architect Niels Torp and several other prominent Norwegian families.
  • C. Tankerness
    Tankerness is a rural settlement on the Orkney Islands of Scotland, known for its agricultural landscape and archaeological sites.
  • D. Skudai
    Skudai is a rapidly developing suburban town in the Malaysian state of Johor, known for housing Universiti Teknologi Malaysia and serving as part of the greater Johor Bahru metropolitan area.
  • E. Rusty Trawler
    Rusty Trawler is a wealthy, socially prominent yet somewhat ridiculous character in Truman Capote’s novella "Breakfast at Tiffany’s."
  • 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_69ca84777560819084cddd999badc1aa completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd986d5af08190a001c5a5ff647d4d completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a44c3c08190a09277737c7a98e0 completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:58 p.m.