Triple

T12942644
Position Surface form Disambiguated ID Type / Status
Subject Cities of the Plain E309672 entity
Predicate follows P134 FINISHED
Object The Crossing E714206 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: The Crossing | Statement: [Cities of the Plain, follows, The Crossing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Crossing
Context triple: [Cities of the Plain, follows, The Crossing]
  • A. The Crossing chosen
    The Crossing is a historical novel by Howard Fast that dramatizes George Washington’s daring 1776 crossing of the Delaware River during the American Revolutionary War.
  • B. The Crossing
    The Crossing is a crime novel by Michael Connelly featuring detective Harry Bosch teaming up with defense attorney Mickey Haller to investigate a complex murder case.
  • C. The Crossing
    The Crossing is a renowned video art installation by Bill Viola that explores themes of transformation and spirituality through slow-motion imagery of a figure engulfed alternately by fire and water.
  • D. The Crossing
    The Crossing is a science fiction television series centered on refugees from a war-torn future seeking asylum in a small American town.
  • E. The Crossing
    The Crossing is a Chinese historical epic film that intertwines the lives of several characters against the backdrop of the 1949 sinking of the Taiping steamer during the Chinese Civil War.
  • 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e1a28688190ab9fd1307bc76b4a completed April 10, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8d9669c819090471eb7e035d83d completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 5:43 p.m.