Triple

T13609762
Position Surface form Disambiguated ID Type / Status
Subject Rachel Green E325157 entity
Predicate parentOf P120 FINISHED
Object Emma Geller-Green E1050623 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: Emma Geller-Green | Statement: [Rachel Green, parentOf, Emma Geller-Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Geller-Green
Context triple: [Rachel Green, parentOf, Emma Geller-Green]
  • A. Emma Geller-Green chosen
    Emma Geller-Green is the daughter of Rachel Green and Ross Geller on the television series "Friends."
  • B. Mona Greenberg
    Mona Greenberg was the longtime wife of acclaimed American actor Karl Malden.
  • C. Emma Rauschenbach
    Emma Rauschenbach, better known as Emma Jung, was a Swiss psychoanalyst and author who significantly contributed to analytical psychology alongside her husband Carl Gustav Jung.
  • D. Elyse Goldstein
    Elyse Goldstein is a Canadian Reform rabbi, feminist, and educator known for her leadership in Jewish learning and advocacy for gender equality in Judaism.
  • E. Sally Greenberg
    Sally Greenberg is a consumer rights advocate and attorney who serves as a leading executive of the National Consumers League, focusing on protecting and promoting consumer interests.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0aa9a1481908c6f92495aff86c6 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ae56e2081909c0fd044ce3730a9 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:50 p.m.