Triple

T20970442
Position Surface form Disambiguated ID Type / Status
Subject Wonderland of Lights E516477 entity
Predicate city P40 FINISHED
Object Marshall NE NERFINISHED

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: Marshall | Statement: [Wonderland of Lights, city, Marshall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marshall
Context triple: [Wonderland of Lights, city, Marshall]
  • A. Marshall
    Marshall is a 2017 biographical legal drama film about a young Thurgood Marshall, directed by Reginald Hudlin and starring Chadwick Boseman.
  • B. Marshall chosen
    Marshall is a small East Texas city known for its historic architecture, role in the Civil War era, and cultural institutions such as Wiley College.
  • C. Marshall
    Marshall is one of the Adirondack High Peaks in New York’s Adirondack Mountains, known for its remote location and challenging, often trailless ascent.
  • D. Marshall
    Marshall is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
  • E. Marshall
    Marshall is a small unincorporated coastal community in Marin County, California, known for its oyster farms along the eastern shore of Tomales Bay.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fb9f53e88190847f93e0bbca6ea0 completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:43 p.m.