Triple

T12807681
Position Surface form Disambiguated ID Type / Status
Subject Luna spacecraft E306186 entity
Predicate hasPart P35 FINISHED
Object Luna 25 E822843 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: Luna 25 | Statement: [Luna spacecraft, hasPart, Luna 25]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luna 25
Context triple: [Luna spacecraft, hasPart, Luna 25]
  • A. Luna 25 chosen
    Luna 25 is a Russian lunar lander mission aimed at conducting scientific research and demonstrating landing technology near the Moon’s south polar region.
  • B. Luna 20
    Luna 20 was a Soviet robotic lunar sample-return mission that successfully collected and returned soil from the Moon’s surface in 1972.
  • C. Chang’e 4
    Chang’e 4 is a Chinese lunar mission best known for achieving the first soft landing and rover exploration on the far side of the Moon.
  • D. Luna 13
    Luna 13 was a Soviet robotic spacecraft that successfully soft-landed on the Moon in 1966 and transmitted panoramic images and data about the lunar surface.
  • E. Luna 10
    Luna 10 was a Soviet spacecraft that became the first artificial satellite to orbit the Moon, marking a major milestone in early lunar exploration.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e808130819080f404b3a7462c2e completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5bc5f688190a6fd3716c8266b2c completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 5:31 p.m.