Triple

T10355747
Position Surface form Disambiguated ID Type / Status
Subject Laban movement analysis E243994 entity
Predicate alsoKnownAs P39 FINISHED
Object LMA
LMA is a comprehensive system for observing, describing, and interpreting human movement developed from the work of choreographer and movement theorist Rudolf Laban.
 E858447 NE FINISHED

How this triple was built (4 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: LMA | Statement: [Laban movement analysis, alsoKnownAs, LMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LMA
Context triple: [Laban movement analysis, alsoKnownAs, LMA]
  • A. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • B. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • C. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • D. LAL
    LAL is the IATA airport code for Lakeland Linder International Airport, a public airport serving Lakeland, Florida.
  • E. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: LMA
Triple: [Laban movement analysis, alsoKnownAs, LMA]
Generated description
LMA is a comprehensive system for observing, describing, and interpreting human movement developed from the work of choreographer and movement theorist Rudolf Laban.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LMA
Target entity description: LMA is a comprehensive system for observing, describing, and interpreting human movement developed from the work of choreographer and movement theorist Rudolf Laban.
  • A. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • B. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • C. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • D. LAL
    LAL is the IATA airport code for Lakeland Linder International Airport, a public airport serving Lakeland, Florida.
  • E. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • F. None of above. chosen

Provenance (5 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e953d4888190b7ca0ac932349dbf completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750a9b4188190a8ecdd9e4d97570b completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618ecb748190a492406eabe590d7 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77057affc8190b420e66560c3dfbd completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, 11:58 a.m.