Triple

T19021801
Position Surface form Disambiguated ID Type / Status
Subject Hello, I Love You E465503 entity
Predicate B-side P15273 FINISHED
Object Love Street NE NERFINISHED

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: Love Street | Statement: [Hello, I Love You, B-side, Love Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Love Street
Context triple: [Hello, I Love You, B-side, Love Street]
  • A. Love Street chosen
    Love Street was a historic football stadium in Paisley, Scotland, best known as the long-time home of St Mirren F.C.
  • B. Green Street
    Green Street is a 2005 British-American drama film about football hooliganism, starring Elijah Wood as an American who becomes involved with a violent West Ham United firm.
  • C. Green Street
    Green Street is a small historic shopping street in the centre of Cambridge, England, known for its mix of independent boutiques and high-street retailers connecting Sidney Street and Trinity Street.
  • D. Green Street
    Green Street is a notable thoroughfare running through San Francisco’s Russian Hill neighborhood, known for its steep grades and classic city views.
  • E. Green Street
    Green Street is a notable city street in Pasadena, California, known for its central location and role in the city's urban layout and traffic flow.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6dfa3c88190a057c3385d680cf8 completed April 20, 2026, 7:33 a.m.
Created at: April 10, 2026, 12:02 p.m.