Triple

T954402
Position Surface form Disambiguated ID Type / Status
Subject Dina bint Abdul-Hamid E20593 entity
Predicate marriageTypeWithHussein P8399 FINISHED
Object arranged marriage LITERAL 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: arranged marriage | Statement: [Dina bint Abdul-Hamid, marriageTypeWithHussein, arranged marriage]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: marriageTypeWithHussein
Context triple: [Dina bint Abdul-Hamid, marriageTypeWithHussein, arranged marriage]
  • A. marriageType chosen
    Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
  • B. houseByMarriage
    Indicates a familial or household relationship established through marriage rather than by blood or direct residence.
  • C. marriagePattern
    Indicates the typical form or structure of a marriage relationship, such as how partners are selected, organized, or related within a social or cultural system.
  • D. maritalBasis
    Indicates that the relationship or status in question is founded on, justified by, or determined due to a marital relationship between the involved entities.
  • E. marriedInto
    Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
  • F. None of above.

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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3da8d508190b56b29d7f235d2c4 completed March 1, 2026, 9:47 p.m.
PD Predicate disambiguation batch_69a4b2a045308190ab94f3adab40db8d completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:40 p.m.