Triple

T27373013
Position Surface form Disambiguated ID Type / Status
Subject Talisa Soto E690378 entity
Predicate modeledForMagazine P163102 FINISHED
Object Mademoiselle
Mademoiselle was an American women’s fashion and lifestyle magazine known for its focus on young, career-oriented women and contemporary style.
 E1771154 NE FINISHED

How this triple was built (3 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: Mademoiselle | Statement: [Talisa Soto, modeledForMagazine, Mademoiselle]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mademoiselle
Triple: [Talisa Soto, modeledForMagazine, Mademoiselle]
Generated description
Mademoiselle was an American women’s fashion and lifestyle magazine known for its focus on young, career-oriented women and contemporary style.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: modeledForMagazine
Context triple: [Talisa Soto, modeledForMagazine, Mademoiselle]
  • A. magazineType
    Indicates the specific category or genre to which a magazine belongs.
  • B. hasPhotographedFor
    Indicates that one entity has taken photographs on behalf of, or as a service for, another entity.
  • C. relationshipToMagazine
    Indicates the type of connection or association an entity has with a particular magazine, such as authorship, editorship, or other defined roles or links.
  • D. magazineRelease
    Indicates the event or relationship in which a magazine is issued or made publicly available on a particular date or through a specific channel.
  • E. modeledBy
    Indicates that one entity serves as a model or representation of another, typically capturing its structure, behavior, or properties.
  • F. None of above. chosen

Provenance (7 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_69ef51ff826081909e42c8e2bfb97941 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f63639a84c81909d700a539b458b42 completed May 2, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7e5fdb4819093fccc56cfff0cae completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a9ef43ac819097d5c47108692c15 completed May 24, 2026, 7:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12ab2c6840819085f11be72866c959 completed May 24, 2026, 7:39 a.m.
PD Predicate disambiguation batch_69f631850ae08190a0ba51e4f1e4ccb3 completed May 2, 2026, 5:16 p.m.
PDg Predicate description generation batch_69f6352df6148190bc10772cd40bd7b3 completed May 2, 2026, 5:32 p.m.
Created at: April 27, 2026, 12:19 p.m.