Triple

T4569662
Position Surface form Disambiguated ID Type / Status
Subject Frozen Worlds E122998 entity
Predicate featuresLocation P7690 FINISHED
Object Greenland E15389 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: Greenland | Statement: [Frozen Worlds, featuresLocation, Greenland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greenland
Context triple: [Frozen Worlds, featuresLocation, Greenland]
  • A. Greenland
    Greenland is a 2020 American disaster thriller film starring Gerard Butler, centered on a family's struggle to survive a catastrophic comet event.
  • B. Greenland chosen
    Greenland is the world’s largest island, an autonomous territory within the Kingdom of Denmark, known for its vast Arctic landscapes and extensive ice sheet.
  • C. Groenlandia
    Groenlandia is a film and television production company known for working on major international projects such as the series "Game of Thrones."
  • D. Grenland
    Grenland is a culturally and historically significant region in southeastern Norway, centered around the industrial towns near the coast and traditionally associated with the county of Telemark.
  • E. Greenland USA
    Greenland USA is a real estate development company known for its major role in large-scale urban projects in the United States, including high-profile mixed-use developments.
  • 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_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58c3eba48190af1fce6e1ca16943 completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3c6806c81908fd374cd4537185e completed March 20, 2026, 11:09 p.m.
Created at: March 20, 2026, 1:10 p.m.