Triple

T2964114
Position Surface form Disambiguated ID Type / Status
Subject Israel E80119 entity
Predicate hasSpouse P13 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: [Israel, hasSpouse, Rachel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel
Context triple: [Israel, hasSpouse, 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. Maria
    Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9958b1e48190a77f37bf63333c5b completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e229afc8190ae634dbfb3ac4313 completed March 11, 2026, 8:56 a.m.
Created at: March 8, 2026, 2:58 p.m.