Triple

T6591691
Position Surface form Disambiguated ID Type / Status
Subject Maryland Route 33 E159374 entity
Predicate hasAbbreviation P43 FINISHED
Object MD 33
MD 33 is a state highway in Maryland that runs through Talbot County, connecting the town of Easton with several communities along the Miles River and Chesapeake Bay.
 E599649 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: MD 33 | Statement: [Maryland Route 33, hasAbbreviation, MD 33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MD 33
Context triple: [Maryland Route 33, hasAbbreviation, MD 33]
  • A. MD 32
    MD 32 is a state highway in Maryland that serves as a major east–west and north–south connector through the central part of the state, linking suburbs, military installations, and key regional routes.
  • B. MD 202
    MD 202 is a state highway in Maryland that connects communities in Prince George’s County, including the area near FedExField and the Capital Beltway.
  • C. MDC
    MDC is a Zimbabwean opposition political party known as the Movement for Democratic Change, which has played a major role in challenging the long-standing rule of ZANU–PF.
  • D. MD
    MD is the station code used to identify Maitland railway station in New South Wales, Australia.
  • E. MD
    MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
  • 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: MD 33
Triple: [Maryland Route 33, hasAbbreviation, MD 33]
Generated description
MD 33 is a state highway in Maryland that runs through Talbot County, connecting the town of Easton with several communities along the Miles River and Chesapeake Bay.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MD 33
Target entity description: MD 33 is a state highway in Maryland that runs through Talbot County, connecting the town of Easton with several communities along the Miles River and Chesapeake Bay.
  • A. MD 32
    MD 32 is a state highway in Maryland that serves as a major east–west and north–south connector through the central part of the state, linking suburbs, military installations, and key regional routes.
  • B. MD 202
    MD 202 is a state highway in Maryland that connects communities in Prince George’s County, including the area near FedExField and the Capital Beltway.
  • C. MDC
    MDC is a Zimbabwean opposition political party known as the Movement for Democratic Change, which has played a major role in challenging the long-standing rule of ZANU–PF.
  • D. MD
    MD is the station code used to identify Maitland railway station in New South Wales, Australia.
  • E. MD
    MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
  • 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_69c688366ce8819083f8883983c0df92 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6aece1f848190a11676e072afb002 completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbba656c81909c3876a8f2f7300e completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd08a9c88190a481d4d3f8e680bf completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdc859cc8190bbae2efc39409021 completed March 27, 2026, 6:34 p.m.
Created at: March 27, 2026, 1:55 p.m.