Triple

T9543157
Position Surface form Disambiguated ID Type / Status
Subject Firelands E230208 entity
Predicate alsoKnownAs P39 FINISHED
Object Fire Lands E230208 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: Fire Lands | Statement: [Firelands, alsoKnownAs, Fire Lands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fire Lands
Context triple: [Firelands, alsoKnownAs, Fire Lands]
  • A. Firelands chosen
    Firelands is a historic region in north-central Ohio originally settled as compensation lands for Connecticut residents whose homes were burned during the American Revolutionary War.
  • B. Skylands
    Skylands is a vast, floating world of islands and magical realms that serves as the primary universe where the Skylanders games and adventures take place.
  • C. Lammas Lands
    Lammas Lands is a riverside meadow and public open space in Godalming, Surrey, known for its traditional grazing land, wildlife habitats, and recreational walking areas.
  • D. Skyland
    Skyland is a mountain resort area in Shenandoah National Park, Virginia, known for its scenic vistas along Skyline Drive.
  • E. Dreamlands
    Dreamlands is a vast, surreal dream-realm in H. P. Lovecraft’s fiction, filled with strange cities, gods, and landscapes that exist parallel to the waking world.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e9be048190bf1f01884ff7c362 completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c6538b08190a9f81304214a876d completed April 4, 2026, 5:37 p.m.
Created at: March 30, 2026, 8:01 p.m.