Triple

T10890003
Position Surface form Disambiguated ID Type / Status
Subject Highcross Leicester E257147 entity
Predicate hasManagementCompany P2469 FINISHED
Object Hammerson E296533 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: Hammerson | Statement: [Highcross Leicester, hasManagementCompany, Hammerson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hammerson
Context triple: [Highcross Leicester, hasManagementCompany, Hammerson]
  • A. Hammerson chosen
    Hammerson is a major British property development and investment company specializing in retail destinations such as shopping centres and retail parks.
  • B. Hatchards
    Hatchards is a historic London bookshop, founded in 1797 and renowned as one of the oldest and most prestigious bookstores in the United Kingdom.
  • C. Hamleys
    Hamleys is a world-famous British toy store chain best known for its flagship multi-storey shop in central London.
  • D. Debenhams
    Debenhams was a major British department store chain offering fashion, beauty, and home goods through high-street locations and online retail.
  • E. Cluett Peabody & Company
    Cluett Peabody & Company was a prominent American clothing manufacturer best known for its Arrow brand shirts and collars and its influential early 20th-century advertising campaigns.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d752041e2c8190b513dc9dc5857fcc completed April 9, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2169ea02c8190addf125ec5adafe8 completed April 17, 2026, 11:16 a.m.
Created at: April 8, 2026, 9:21 p.m.