Triple

T35401843
Position Surface form Disambiguated ID Type / Status
Subject My Education E1023253 entity
Predicate hasMainRelationshipType P24749 FINISHED
Object same-sex relationship 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: same-sex relationship | Statement: [My Education, hasMainRelationshipType, same-sex relationship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMainRelationshipType
Context triple: [My Education, hasMainRelationshipType, same-sex relationship]
  • A. hasCentralRelationshipType chosen
    Indicates that there exists a primary or most significant type of relationship that characterizes how two entities are related to each other.
  • B. hasRelationships
    Indicates that an entity is connected to one or more other entities through specified types of relationships.
  • C. hasKeyRelationship
    Indicates a relationship where one entity serves as a key (e.g., identifier, access token, or primary reference) that grants access to, controls, or uniquely identifies another entity.
  • D. hasRelation
    Indicates that there exists some specified relationship or association between two entities.
  • E. hasSymbolicRelationshipType
    Indicates that there exists a symbolic (non-literal) relationship of a specified type between two entities.
  • 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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a022348ae2881908eae1be79b6f6ff6 completed May 11, 2026, 6:43 p.m.
PD Predicate disambiguation batch_6a0220beb6b08190981fb86363757517 completed May 11, 2026, 6:32 p.m.
Created at: May 3, 2026, 4:03 p.m.