Triple

T15961806
Position Surface form Disambiguated ID Type / Status
Subject Matt Ross E387078 entity
Predicate employer P7 FINISHED
Object HBO (for Big Love) E18702 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: HBO (for Big Love) | Statement: [Matt Ross, employer, HBO (for Big Love)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HBO (for Big Love)
Context triple: [Matt Ross, employer, HBO (for Big Love)]
  • A. HBO chosen
    HBO is a premium American television and streaming network known for producing influential, high-quality original series, films, and documentaries such as "The Sopranos," "Game of Thrones," and "Succession."
  • B. HBO
    HBO is the Dutch sector of universities of applied sciences that focuses on professionally oriented higher education and practical training.
  • C. HBO2
    HBO2 is a secondary premium cable and streaming channel from HBO that offers additional movies, series, and original programming alongside the main HBO service.
  • D. Showtime
    Showtime is an American premium cable and streaming network known for its original, often edgy series, films, and sports programming.
  • E. HBO Pictures
    HBO Pictures was the original feature film production arm of the HBO cable network, known for producing made-for-television movies and miniseries.
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15700651c819091c1cc4f60894c35 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe827d248190adbfd41f55638ebd completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:53 a.m.