Triple

T8146213
Position Surface form Disambiguated ID Type / Status
Subject Watertown Dam E190217 entity
Predicate near P350 FINISHED
Object Watertown Square E34563 NE FINISHED

How this triple was built (2 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: Watertown Square | Statement: [Watertown Dam, near, Watertown Square]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Watertown Square
Context triple: [Watertown Dam, near, Watertown Square]
  • A. Watertown Square chosen
    Watertown Square is a major transit and commercial hub in Watertown, Massachusetts, functioning as a key connection point for multiple MBTA bus routes and local activity.
  • B. Mattapan Square
    Mattapan Square is a central commercial and transit hub in Boston’s Mattapan neighborhood, known for its diverse community, local businesses, and key transportation connections.
  • C. Warren Square
    Warren Square is one of Savannah, Georgia’s historic public squares, known for its landscaped green space and surrounding period architecture within the city’s famed grid plan.
  • D. Woods Square
    Woods Square is a mixed-use commercial development in Singapore’s Woodlands area that features office spaces integrated with retail and lifestyle amenities.
  • E. Quincy Market
    Quincy Market is a historic 19th-century marketplace in downtown Boston, now a popular destination for food, shopping, and tourism.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82be7ba8819087de0147e9292c83 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4447dbc48190affb0f34f6c85f5a completed March 31, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced2bba08819080c4a2bb8c9ba1f2 completed April 1, 2026, 10:02 a.m.
Created at: March 30, 2026, 5:36 p.m.