Triple

T10144009
Position Surface form Disambiguated ID Type / Status
Subject UR-100 E231655 entity
Predicate successor P78 FINISHED
Object UR-100N E447396 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: UR-100N | Statement: [UR-100, successor, UR-100N]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UR-100N
Context triple: [UR-100, successor, UR-100N]
  • A. UR-100NUTTKh chosen
    The UR-100NUTTKh is a Soviet-designed intercontinental ballistic missile (ICBM) deployed in Russian strategic nuclear forces.
  • B. MR-UR-100
    MR-UR-100 was a Soviet intercontinental ballistic missile (ICBM) system developed during the Cold War as part of the USSR’s strategic nuclear forces.
  • C. Ibaraki Robots
    Ibaraki Robots is a professional Japanese basketball team based in Ibaraki Prefecture that competes in the B.League.
  • D. ND-100
    ND-100 is a 16-bit minicomputer series developed by Norwegian company Norsk Data, widely used in the 1970s and 1980s for technical and scientific computing.
  • E. Atlas humanoid robot
    The Atlas humanoid robot is a highly advanced, bipedal research platform developed by Boston Dynamics for exploring agile, human-like mobility and manipulation in complex environments.
  • 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_69ca848364f881908a24366a6feec1db completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdeb28a1708190b46499dbe51a694a completed April 2, 2026, 4:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e618b0bc8190bc1d6f15dac2708e completed April 5, 2026, 10:45 p.m.
Created at: March 30, 2026, 9:07 p.m.