Triple

T7328280
Position Surface form Disambiguated ID Type / Status
Subject Phélippeaux E168929 entity
Predicate placeOfActivity P1527 FINISHED
Object Acre E57659 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: Acre | Statement: [Phélippeaux, placeOfActivity, Acre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Acre
Context triple: [Phélippeaux, placeOfActivity, Acre]
  • A. Acre chosen
    Acre is an ancient port city on the Mediterranean coast of present-day Israel, renowned for its well-preserved Crusader and Ottoman architecture and its long, strategic history.
  • B. Acre (state)
    Acre is a remote, heavily forested state in Brazil’s western Amazon region, known for its vast rainforest, rubber-tapping history, and rich Indigenous cultures.
  • C. Felda
    Felda is a small river in central Germany that flows through Hesse and Thuringia before joining the Werra.
  • D. Luas
    Luas is Dublin’s modern light rail tram system, providing frequent urban and suburban public transport across the city and its surrounding areas.
  • E. Amapro
    Amapro is a Japanese production company known for its involvement in creating television and film projects such as the crime drama series "Tokyo Vice."
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0a879b88190bef0fb6cbae411ff completed March 27, 2026, 9:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ef11f76881909d802942c4013509 completed March 28, 2026, 3:09 p.m.
Created at: March 27, 2026, 3:03 p.m.