Triple

T9455873
Position Surface form Disambiguated ID Type / Status
Subject Mountain Line Transit Authority E228011 entity
Predicate hasAbbreviation P43 FINISHED
Object MLTA
MLTA is the abbreviation for Mountain Line Transit Authority, a public transportation agency that operates bus services.
 E801020 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: MLTA | Statement: [Mountain Line Transit Authority, hasAbbreviation, MLTA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MLTA
Context triple: [Mountain Line Transit Authority, hasAbbreviation, MLTA]
  • A. MLT
    MLT is the three-letter ISO 3166-1 alpha-3 country code assigned to Malta.
  • B. TMTA
    TMTA was the stock ticker symbol for Transmeta Corporation, a now-defunct American semiconductor company known for its low-power x86-compatible microprocessors.
  • C. LTAJ
    LTAJ is the ICAO airport code for Oğuzeli Airport, an airfield serving the Gaziantep region in southeastern Turkey.
  • D. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • E. MTCA
    MTCA is Washington State’s Model Toxics Control Act, a key environmental law governing the cleanup of contaminated sites and the management of hazardous substances.
  • 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: MLTA
Triple: [Mountain Line Transit Authority, hasAbbreviation, MLTA]
Generated description
MLTA is the abbreviation for Mountain Line Transit Authority, a public transportation agency that operates bus services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MLTA
Target entity description: MLTA is the abbreviation for Mountain Line Transit Authority, a public transportation agency that operates bus services.
  • A. MLT
    MLT is the three-letter ISO 3166-1 alpha-3 country code assigned to Malta.
  • B. TMTA
    TMTA was the stock ticker symbol for Transmeta Corporation, a now-defunct American semiconductor company known for its low-power x86-compatible microprocessors.
  • C. LTAJ
    LTAJ is the ICAO airport code for Oğuzeli Airport, an airfield serving the Gaziantep region in southeastern Turkey.
  • D. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • E. MTCA
    MTCA is Washington State’s Model Toxics Control Act, a key environmental law governing the cleanup of contaminated sites and the management of hazardous substances.
  • 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_69ca843b123881909b0e60028475d12d completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f8f7e1481909318e473ab4d6460 completed April 1, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122849fec81908a8e7363d6bab4ed completed April 4, 2026, 2:39 p.m.
NEDg Description generation batch_69d123f710988190a876fab3a1e226d3 completed April 4, 2026, 2:45 p.m.
NED2 Entity disambiguation (via description) batch_69d1252cd7508190a7d11fce51960290 completed April 4, 2026, 2:50 p.m.
Created at: March 30, 2026, 7:52 p.m.