Triple

T2114994
Position Surface form Disambiguated ID Type / Status
Subject A44 E42589 entity
Predicate connects P390 FINISHED
Object Worcester E112481 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: Worcester | Statement: [A44, connects, Worcester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Worcester
Context triple: [A44, connects, Worcester]
  • A. Worcester
    Worcester is a large agricultural and commercial town in South Africa’s Western Cape, known for its vineyards, fruit farming, and surrounding mountain scenery.
  • B. Worcester, Massachusetts
    Worcester, Massachusetts is a major city in central Massachusetts known as a historic industrial and educational hub often called the "Heart of the Commonwealth."
  • C. Ipswich
    Ipswich is a historic town and port in Suffolk, England, known as one of the country’s oldest continuously inhabited settlements.
  • D. Worcester, England chosen
    Worcester, England is a historic cathedral city in the West Midlands of England, known for its medieval architecture, role in the English Civil War, and as the namesake of Worcester, Massachusetts.
  • E. Fitchburg
    Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb0724e08190a0a4210d86261d6d completed March 7, 2026, 5:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5194abec8190aab8b7a9ef98da92 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:43 p.m.