Triple

T9218403
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Province E221297 entity
Predicate containsTown P847 FINISHED
Object Messancy E569989 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: Messancy | Statement: [Luxembourg Province, containsTown, Messancy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Messancy
Context triple: [Luxembourg Province, containsTown, Messancy]
  • A. Messancy chosen
    Messancy is a municipality in the province of Luxembourg in southern Belgium, located near the border with Luxembourg and France.
  • B. Manfalut
    Manfalut is a city in Upper Egypt known as an agricultural and commercial center within the Asyut region along the Nile.
  • C. Exameron
    Exameron is a theological and exegetical work by Saint Ambrose of Milan that offers a Christian commentary on the six days of Creation in the Book of Genesis.
  • D. Sanniquellie
    Sanniquellie is a town in northeastern Liberia that serves as an administrative and commercial center in the region.
  • E. Heed
    Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda730f688190b64b2cc8c4898ac3 completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0662427dc81908cb9bfacc5b9e0f5 completed April 4, 2026, 1:15 a.m.
Created at: March 30, 2026, 7:27 p.m.