Triple

T3383934
Position Surface form Disambiguated ID Type / Status
Subject Massachusetts Contingency Plan E71250 entity
Predicate hasAbbreviation P43 FINISHED
Object AUL
AUL is an abbreviation used in Massachusetts environmental regulation to denote an Activity and Use Limitation, a legal restriction placed on how a contaminated property may be used.
 E352773 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: AUL | Statement: [Massachusetts Contingency Plan, hasAbbreviation, AUL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AUL
Context triple: [Massachusetts Contingency Plan, hasAbbreviation, AUL]
  • A. AUL
    AUL is the ICAO airline designator assigned to the Russian carrier Smartavia.
  • B. ALO
    ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
  • C. ALO
    ALO is the Arab Labor Organization, a specialized Arab League body that promotes labor standards, employment policies, and workers’ rights across Arab countries.
  • D. AÜ
    AÜ is the commonly used abbreviation for Ankara University, a major public research university in Turkey’s capital city.
  • E. AAL
    AAL is the ICAO airline designator used in aviation to identify American Airlines in flight operations and air traffic control.
  • 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: AUL
Triple: [Massachusetts Contingency Plan, hasAbbreviation, AUL]
Generated description
AUL is an abbreviation used in Massachusetts environmental regulation to denote an Activity and Use Limitation, a legal restriction placed on how a contaminated property may be used.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AUL
Target entity description: AUL is an abbreviation used in Massachusetts environmental regulation to denote an Activity and Use Limitation, a legal restriction placed on how a contaminated property may be used.
  • A. AUL
    AUL is the ICAO airline designator assigned to the Russian carrier Smartavia.
  • B. ALO
    ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
  • C. ALO
    ALO is the Arab Labor Organization, a specialized Arab League body that promotes labor standards, employment policies, and workers’ rights across Arab countries.
  • D. AÜ
    AÜ is the commonly used abbreviation for Ankara University, a major public research university in Turkey’s capital city.
  • E. AAL
    AAL is the ICAO airline designator used in aviation to identify American Airlines in flight operations and air traffic control.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5ec85d08190b28110157c39435f completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b33452d79081909bf6955289e0dece completed March 12, 2026, 9:46 p.m.
NEDg Description generation batch_69b334f75e708190aed8b388c9ea55d2 completed March 12, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_69b3359ab56881908e247ba54c7dd6c7 completed March 12, 2026, 9:52 p.m.
Created at: March 8, 2026, 3:14 p.m.