Triple

T9633554
Position Surface form Disambiguated ID Type / Status
Subject Suhaila Ng E232865 entity
Predicate givenName P17 FINISHED
Object Suhaila E812249 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: Suhaila | Statement: [Suhaila Ng, givenName, Suhaila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suhaila
Context triple: [Suhaila Ng, givenName, Suhaila]
  • A. Suhaila chosen
    Suhaila is the young girl protagonist of the children's book "Ladder to the Moon," who embarks on a magical, intergenerational journey with her grandmother to explore themes of compassion and connection.
  • B. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • C. Fahdah
    Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
  • D. Karima
    Karima is a town in northern Sudan known as a gateway to the ancient Nubian archaeological area around Gebel Barkal and the Napatan sites.
  • E. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b28ce2c819086d3c6e4e6ea95a7 completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189fa706c819080e8ac2411f57d93 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:11 p.m.