Triple

T9723454
Position Surface form Disambiguated ID Type / Status
Subject Princess Salha bint Asem E235540 entity
Predicate familyName P18 FINISHED
Object bint Asem E668294 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: bint Asem | Statement: [Princess Salha bint Asem, familyName, bint Asem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: bint Asem
Context triple: [Princess Salha bint Asem, familyName, bint Asem]
  • A. bint Asem chosen
    Bint Asem is a member of the Jordanian royal family, known as a Hashemite princess connected to the line of King Abdullah II.
  • B. Asan
    Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
  • C. Âsım
    Âsım is a long narrative poem by Turkish poet Mehmet Âkif Ersoy, included as one of the books in his celebrated poetry collection Safahat.
  • D. Asmal
    Asmal is a surname most notably associated with Kader Asmal, a prominent South African anti-apartheid activist, academic, and government minister.
  • E. Aasai
    Aasai is a 1995 Tamil romantic thriller film that gained widespread recognition for its gripping storyline and for significantly boosting actor Ajith Kumar’s early career.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e75abd48190a6e6679ec51496e8 completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19fa5a8e48190b7b1742eb6c3b81e completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:20 p.m.