Triple

T3357856
Position Surface form Disambiguated ID Type / Status
Subject Rachel Brosnahan E70647 entity
Predicate givenName P17 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: [Rachel Brosnahan, givenName, Rachel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel
Context triple: [Rachel Brosnahan, givenName, 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 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.
  • C. Sarah
    Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
  • D. Sarah
    Sarah is the birth name of Margaret Fuller, the 19th-century American journalist, critic, and women's rights advocate associated with the Transcendentalist movement.
  • E. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb244435c81908e35d2aa36ec4f46 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3545ea1b08190ad84b7e5f70b4d2e completed March 13, 2026, 12:03 a.m.
Created at: March 8, 2026, 3:13 p.m.