Triple

T7831375
Position Surface form Disambiguated ID Type / Status
Subject Saint Louis Art Museum E181576 entity
Predicate hasAbbreviation P43 FINISHED
Object SLAM E181576 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: SLAM | Statement: [Saint Louis Art Museum, hasAbbreviation, SLAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SLAM
Context triple: [Saint Louis Art Museum, hasAbbreviation, SLAM]
  • A. SLAM chosen
    SLAM is a major art museum in St. Louis, Missouri, renowned for its extensive collection spanning thousands of years and diverse cultures.
  • B. SLAMjamz
    SLAMjamz is an independent record label founded by Chuck D of Public Enemy, known for releasing politically conscious hip-hop and related music.
  • C. Monte Carlo localization
    Monte Carlo localization is a probabilistic robotics algorithm that uses particle filters to estimate a robot’s pose within a known map based on noisy sensor and motion data.
  • D. Pami
    Pami was a pharaoh of Egypt’s Twenty-second Dynasty, a Libyan-origin ruler known from the Third Intermediate Period.
  • E. CMU Highly Intelligent Mobile Platform
    CMU Highly Intelligent Mobile Platform (CHIMP) is a sophisticated humanoid robot developed at Carnegie Mellon University for advanced mobility, manipulation, and autonomous operation in challenging 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_69ca8284a25c8190a1a20afad30da792 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb0647848081908d74e09f52d0919e completed March 30, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a906b908190a204779950555edc completed March 31, 2026, 5:24 a.m.
Created at: March 30, 2026, 4:44 p.m.