Triple

T10252547
Position Surface form Disambiguated ID Type / Status
Subject The Large Piece of Turf E240378 entity
Predicate location P40 FINISHED
Object Albertina E854856 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: Albertina | Statement: [The Large Piece of Turf, location, Albertina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albertina
Context triple: [The Large Piece of Turf, location, Albertina]
  • A. Albertina
    Albertina was the historic University of Königsberg, a prominent Prussian center of learning and research founded in the 16th century.
  • B. Albertina chosen
    Albertina is a renowned art museum and graphic arts collection in Vienna, Austria, famous for its vast holdings of prints and drawings by masters such as Dürer, Michelangelo, and Picasso.
  • C. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • D. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • E. Catharina
    Catharina of Württemberg was a 19th-century German princess who became Queen consort of Westphalia through her marriage to Jérôme Bonaparte, Napoleon’s youngest brother.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d23f106c81909c1ce20a2ffa86ea completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d794ad73508190880a1030d483f5a8 completed April 9, 2026, 11:59 a.m.
Created at: April 6, 2026, 11:29 a.m.