Triple

T8103379
Position Surface form Disambiguated ID Type / Status
Subject film "Empire" E189166 entity
Predicate hasCrewMember P42937 FINISHED
Object Marie Desert E189166 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: Marie Desert | Statement: [film "Empire", hasCrewMember, Marie Desert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marie Desert
Context triple: [film "Empire", hasCrewMember, Marie Desert]
  • A. Marie Desert chosen
    Marie Desert is a film professional credited as an assistant on the movie "Empire."
  • B. Błędów Desert
    Błędów Desert is a rare inland sand desert in southern Poland, known for its extensive dunes and unique, almost desert-like landscape.
  • C. Deserta Grande
    Deserta Grande is the largest and main island of the Desertas Islands, a small uninhabited Portuguese archipelago southeast of Madeira known for its rugged terrain and protected wildlife.
  • D. Kalimari Desert
    Kalimari Desert is a Wild West–themed racetrack in the Mario Kart series, characterized by its sandy terrain and a central railroad crossing with an active train obstacle.
  • E. Katpana Desert
    Katpana Desert is a high-altitude cold desert near Skardu in Pakistan’s Gilgit-Baltistan region, known for its striking sand dunes set against snow-capped mountains.
  • 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_69ca82b886d88190a9cba0d5a4a27521 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42bf1cb0819099dda4f050f8e95e completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc642095a08190bcf90e6470e127cc completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:31 p.m.