Triple

T28106585
Position Surface form Disambiguated ID Type / Status
Subject People's Park (Shanghai) E710379 entity
Predicate marriageMarketFeature P175329 FINISHED
Object paper advertisements with personal information 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: paper advertisements with personal information | Statement: [People's Park (Shanghai), marriageMarketFeature, paper advertisements with personal information]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: marriageMarketFeature
Context triple: [People's Park (Shanghai), marriageMarketFeature, paper advertisements with personal information]
  • A. marriageCharacterization
    Indicates how a marriage is described, evaluated, or characterized in terms of its qualities, dynamics, or nature.
  • B. marriesFor
    Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
  • C. desiredMarriageWith
    Indicates that one entity wishes to enter into a marital relationship with another entity.
  • D. spouseCharacteristic
    Indicates that a particular characteristic, trait, or attribute is associated with a person’s spouse within the relationship.
  • E. seeksToArrangeMarriageFor
    Indicates an entity’s intention or effort to organize or facilitate a marriage for another entity.
  • F. None of above. chosen

Provenance (4 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_69ef9b71fdb081908b4a61cd7ff147c1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6d1d916f881909575c2b22c416a5b completed May 3, 2026, 4:40 a.m.
PD Predicate disambiguation batch_69f6cfe2183481908ae4e85a59c66f69 completed May 3, 2026, 4:32 a.m.
PDg Predicate description generation batch_69f6d0d331dc8190be5aa6bfc6365e67 completed May 3, 2026, 4:36 a.m.
Created at: April 27, 2026, 9:08 p.m.