Triple

T596365
Position Surface form Disambiguated ID Type / Status
Subject Route 2 (Massachusetts) E17391 entity
Predicate abbreviation P43 FINISHED
Object MA 2
MA 2 is a major east–west state highway in Massachusetts that connects the Boston area with the north-central and western parts of the state.
 E74362 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: MA 2 | Statement: [Route 2 (Massachusetts), abbreviation, MA 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MA 2
Context triple: [Route 2 (Massachusetts), abbreviation, MA 2]
  • A. MA 16
    MA 16 is a state highway designation for a major east–west route in Massachusetts that passes through several cities and suburbs near Boston.
  • B. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • C. MA
    MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
  • D. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • E. MAA
    MAA is the acronym for the Maryland Aviation Administration, the state agency that oversees and manages Maryland’s public-use airports, including Baltimore/Washington International Thurgood Marshall Airport.
  • 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: MA 2
Triple: [Route 2 (Massachusetts), abbreviation, MA 2]
Generated description
MA 2 is a major east–west state highway in Massachusetts that connects the Boston area with the north-central and western parts of the state.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MA 2
Target entity description: MA 2 is a major east–west state highway in Massachusetts that connects the Boston area with the north-central and western parts of the state.
  • A. MA 16
    MA 16 is a state highway designation for a major east–west route in Massachusetts that passes through several cities and suburbs near Boston.
  • B. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • C. MA
    MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
  • D. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • E. MAA
    MAA is the acronym for the Maryland Aviation Administration, the state agency that oversees and manages Maryland’s public-use airports, including Baltimore/Washington International Thurgood Marshall Airport.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bd3e5e08190be95cb2009aad42d completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c766508190ae39b6e254a07bc3 completed March 2, 2026, 4:57 a.m.
NEDg Description generation batch_69a5194215848190874442451c32a10b completed March 2, 2026, 4:59 a.m.
NED2 Entity disambiguation (via description) batch_69a519d2e46881909d00ff279bd4a13e completed March 2, 2026, 5:02 a.m.
Created at: March 1, 2026, 7:33 p.m.