Triple

T14683575
Position Surface form Disambiguated ID Type / Status
Subject Ramah E344848 entity
Predicate associatedWith P37 FINISHED
Object Rachel E69959 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: Rachel | Statement: [Ramah, associatedWith, Rachel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel
Context triple: [Ramah, associatedWith, Rachel]
  • A. Rachel
    Rachel is the famous bronze piggy bank sculpture and unofficial mascot of Seattle’s Pike Place Market, known for collecting donations for local social services.
  • B. Rachel
    Rachel is a feminine given name of Hebrew origin meaning "ewe," historically associated with the biblical matriarch and widely used in many cultures.
  • C. Rachel
    Rachel is a fictional character portrayed by French actress Clémence Poésy, known for her roles in film and television dramas.
  • D. Rachel
    Rachel is a central protagonist in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s broadcast journalists.
  • E. Rachel chosen
    Rachel is a prominent biblical matriarch in the Book of Genesis, known as Jacob’s beloved wife and the mother of Joseph and Benjamin.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb56a51ec8190941684fd562a7182 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde18592088190892ae1cc371165be completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.