Triple

T8404922
Position Surface form Disambiguated ID Type / Status
Subject Maine State Route 102 E198470 entity
Predicate abbreviation P43 FINISHED
Object ME 102
ME 102 is a state highway in Maine that runs through Mount Desert Island, providing access to Acadia National Park and several coastal communities.
 E732575 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: ME 102 | Statement: [Maine State Route 102, abbreviation, ME 102]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ME 102
Context triple: [Maine State Route 102, abbreviation, ME 102]
  • A. ME 100
    ME 100 is a state highway in Maine that serves as a major north–south route connecting several communities and providing an alternative to Interstate 95.
  • B. ME 152
    ME 152 is a state highway in Maine that serves as a regional connector route between local communities.
  • C. MEC
    MEC is the commonly used acronym for Uruguay’s Ministry of Education and Culture, the national body responsible for educational policy and cultural affairs.
  • D. IEN 41
    IEN 41 is an early Internet Experiment Note documenting research and design considerations in the formative stages of the ARPANET/Internet protocols.
  • E. ENGM
    ENGM is the ICAO airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital region.
  • 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: ME 102
Triple: [Maine State Route 102, abbreviation, ME 102]
Generated description
ME 102 is a state highway in Maine that runs through Mount Desert Island, providing access to Acadia National Park and several coastal communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ME 102
Target entity description: ME 102 is a state highway in Maine that runs through Mount Desert Island, providing access to Acadia National Park and several coastal communities.
  • A. ME 100
    ME 100 is a state highway in Maine that serves as a major north–south route connecting several communities and providing an alternative to Interstate 95.
  • B. ME 152
    ME 152 is a state highway in Maine that serves as a regional connector route between local communities.
  • C. MEC
    MEC is the commonly used acronym for Uruguay’s Ministry of Education and Culture, the national body responsible for educational policy and cultural affairs.
  • D. IEN 41
    IEN 41 is an early Internet Experiment Note documenting research and design considerations in the formative stages of the ARPANET/Internet protocols.
  • E. ENGM
    ENGM is the ICAO airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital region.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83116bf48190894bd5d5465520ef completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02f8596c8190a61b6f1ffd5a609c completed April 2, 2026, 5:47 a.m.
NEDg Description generation batch_69ce077f25648190b9a95fb72f5b4f8c completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce08e192088190ad8170b1bedd568d completed April 2, 2026, 6:12 a.m.
Created at: March 30, 2026, 6:05 p.m.