Triple

T11871433
Position Surface form Disambiguated ID Type / Status
Subject ISS US Orbital Segment E282415 entity
Predicate includesModule P49317 FINISHED
Object Columbus E921066 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: Columbus | Statement: [ISS US Orbital Segment, includesModule, Columbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Columbus
Context triple: [ISS US Orbital Segment, includesModule, Columbus]
  • A. Columbus
    Columbus is a major city in western Georgia located on the Chattahoochee River, known for its military base Fort Moore (formerly Fort Benning) and its role as a regional economic and cultural center.
  • B. Columbus
    Columbus is a city in eastern Mississippi known for its historic architecture, role in the American Civil War, and as part of the Golden Triangle region.
  • C. Columbus
    Columbus is the cautious, rule-obsessed protagonist and narrator of the post-apocalyptic comedy film "Zombieland."
  • D. Columbus chosen
    Columbus is the European Space Agency’s research laboratory module attached to the International Space Station, used for a wide range of scientific experiments in microgravity.
  • E. Columbus
    Columbus is the capital and largest city of Ohio, known for its diverse economy, major universities, and vibrant arts and sports scenes.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be18b7d48190b7fb1c3a67a891ed completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0d2818c8190a1bea5f1fc8a9f59 completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:43 p.m.