Triple

T5519565
Position Surface form Disambiguated ID Type / Status
Subject Laeken E144770 entity
Predicate contains P35 FINISHED
Object Heysel Plateau E235402 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: Heysel Plateau | Statement: [Laeken, contains, Heysel Plateau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heysel Plateau
Context triple: [Laeken, contains, Heysel Plateau]
  • A. Heysel Plateau chosen
    The Heysel Plateau is a prominent area in northern Brussels known for hosting major exhibition halls, the Atomium landmark, and various cultural and recreational facilities.
  • B. Murnau Moor
    Murnau Moor is a large, ecologically significant bog and nature reserve in Bavaria, Germany, known for its unique wetland landscapes and biodiversity.
  • C. Hallein
    Hallein is a historic town in the Austrian state of Salzburg, known for its former salt mines and picturesque location along the Salzach River.
  • D. Telegrafenberg hill
    Telegrafenberg hill is a historic science campus in Potsdam, Germany, known for hosting several prominent research institutes and observatories.
  • E. Havelterberg
    Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f6eb604819092e9b2207dc741a9 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027e57ed88190b2ff3245226851d1 completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:33 p.m.