Triple

T27034020

Position	Surface form	Disambiguated ID	Type / Status
Subject	Miss Universe 1987	`E681002`	entity
Predicate	missCongenialityWinner	`P161789`	FINISHED
Object	Patricia López Ruiz Patricia López Ruiz is a beauty pageant titleholder best known for winning the Miss Congeniality award at the Miss Universe 1987 competition.	`E1806774`	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: Patricia López Ruiz | Statement: [Miss Universe 1987, missCongenialityWinner, Patricia López Ruiz]

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: Patricia López Ruiz
Triple: [Miss Universe 1987, missCongenialityWinner, Patricia López Ruiz]

Generated description

Patricia López Ruiz is a beauty pageant titleholder best known for winning the Miss Congeniality award at the Miss Universe 1987 competition.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: missCongenialityWinner
Context triple: [Miss Universe 1987, missCongenialityWinner, Patricia López Ruiz]

A. Diva
Indicates that an entity is characterized as a celebrated but temperamental performer, often demanding special treatment or attention in their professional context.
B. sixthWomanOfTheYear
Indicates that the subject is recognized as the sixth individual to receive the "Woman of the Year" title or honor in a given sequence or context.
C. bestCastingWinner
Indicates that the subject has won an award or recognition for delivering the best casting in a given context or competition.
D. الزوجة
Indicates that one entity is the wife (spouse in a marital relationship) of another entity.
E. مجال الشهرة
Indicates the domain or field in which an entity is renowned or widely recognized.
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_69eeeb5566f08190813daf896fa3da04`	completed	April 27, 2026, 4:51 a.m.
NER	Named-entity recognition	`batch_69f6223870308190a016b76902bcf6d4`	completed	May 2, 2026, 4:11 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a15d7719698819096c1a27507cd1b92`	completed	May 26, 2026, 5:25 p.m.
NEDg	Description generation	`batch_6a15e027b5ac8190895de49f44f96e09`	completed	May 26, 2026, 6:02 p.m.
NED2	Entity disambiguation (via description)	`batch_6a15e07f86748190bedcf4ae291748b9`	completed	May 26, 2026, 6:03 p.m.
PD	Predicate disambiguation	`batch_69f61b3ee7b08190a0a1bc5d26b757aa`	completed	May 2, 2026, 3:41 p.m.
PDg	Predicate description generation	`batch_69f61f109ef48190873bfe18638d2046`	completed	May 2, 2026, 3:58 p.m.

Created at: April 27, 2026, 7:15 a.m.