Triple

T16026662
Position Surface form Disambiguated ID Type / Status
Subject Mundaneum E388733 entity
Predicate locatedIn P40 FINISHED
Object Mons E113627 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: Mons | Statement: [Mundaneum, locatedIn, Mons]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mons
Context triple: [Mundaneum, locatedIn, Mons]
  • A. Mons chosen
    Mons is a Belgian town historically significant as the site of a major World War I battle in 1914, where British forces, including the Coldstream Guards, first engaged the German army on the Western Front.
  • B. Montet
    Montet is a French surname most notably borne by archaeologist Pierre Montet, renowned for his discoveries in the royal necropolis of Tanis in Egypt.
  • C. La Mongie
    La Mongie is a French Pyrenean ski resort village known as a gateway to the Pic du Midi de Bigorre and its observatory.
  • D. Eyraud
    Eyraud is a French surname most notably borne by Eugène Eyraud, a 19th-century missionary known for his work on Easter Island.
  • E. Muntei
    Muntei is a village in Indonesia’s Mentawai Islands that gained tragic prominence after being heavily impacted by the 2010 Mentawai earthquake and tsunami.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:56 a.m.