Triple

T12790341
Position Surface form Disambiguated ID Type / Status
Subject Highland Branch (Green Line D) E305741 entity
Predicate hasStation P35 FINISHED
Object Woodland
Woodland is a light rail station on Boston’s MBTA Green Line D branch serving the Newton area.
 E1002787 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: Woodland | Statement: [Highland Branch (Green Line D), hasStation, Woodland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woodland
Context triple: [Highland Branch (Green Line D), hasStation, Woodland]
  • A. Woodland
    Woodland is a small city located in Talbot County, Georgia, in the United States.
  • B. Woodland
    Woodland is a small rural community located in the state of Maine in the United States.
  • C. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • D. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • E. Woodland
    Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
  • 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: Woodland
Triple: [Highland Branch (Green Line D), hasStation, Woodland]
Generated description
Woodland is a light rail station on Boston’s MBTA Green Line D branch serving the Newton area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woodland
Target entity description: Woodland is a light rail station on Boston’s MBTA Green Line D branch serving the Newton area.
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • C. Woodland
    Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
  • D. Woodland
    Woodland is a small city located in Talbot County, Georgia, in the United States.
  • E. Woodland
    Woodland is a small rural community located in the state of Maine in the United States.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6a61f48190972e241e70bc392c completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68508e4488190bb57a1ade93987ab completed May 2, 2026, 11:13 p.m.
NEDg Description generation batch_69f687ae18c08190a94dca38bb69d10f completed May 2, 2026, 11:24 p.m.
NED2 Entity disambiguation (via description) batch_69f68884ed348190a1b2c89b1d655fa9 completed May 2, 2026, 11:28 p.m.
Created at: April 9, 2026, 5:30 p.m.