Triple

T35707232

Position	Surface form	Disambiguated ID	Type / Status
Subject	2016 Wimbledon Championships	`E1031750`	entity
Predicate	girlsDoublesChampions	`P184078`	FINISHED
Object	Usue Maitane Arconada Usue Maitane Arconada is an American professional tennis player known for her success on the junior circuit and subsequent competition on the ITF Women's World Tennis Tour.	`E2151286`	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: Usue Maitane Arconada | Statement: [2016 Wimbledon Championships, girlsDoublesChampions, Usue Maitane Arconada]

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: Usue Maitane Arconada
Triple: [2016 Wimbledon Championships, girlsDoublesChampions, Usue Maitane Arconada]

Generated description

Usue Maitane Arconada is an American professional tennis player known for her success on the junior circuit and subsequent competition on the ITF Women's World Tennis Tour.

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

Target predicate: girlsDoublesChampions
Context triple: [2016 Wimbledon Championships, girlsDoublesChampions, Usue Maitane Arconada]

A. boysDoublesChampions
Indicates that the related entities are the winners of a boys’ doubles championship event.
B. girlsSinglesChampion
Indicates that the subject is the winner of a girls’ singles championship event.
C. mixedDoublesChampions
Indicates that the related entities together won a mixed doubles championship in a given event or competition.
D. grandSlamDoublesTitles
Indicates the number of Grand Slam tennis doubles titles an entity has won.
E. AustralianOpenDoublesChampion
Indicates that the subject is the winner of the doubles competition at the Australian Open tennis tournament for a given year.
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_69f76e0d393c8190b6303c64408736db`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_69f7aaabb58c8190bf81673608ecfb6e`	completed	May 3, 2026, 8:06 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a38729dc0988190b94f61bf98787ca6`	completed	June 21, 2026, 11:24 p.m.
NEDg	Description generation	`batch_6a38730bbf348190b9ad5a1ef6a659a8`	completed	June 21, 2026, 11:26 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3873fd9ccc8190ac41f5aaf772bde6`	completed	June 21, 2026, 11:30 p.m.
PD	Predicate disambiguation	`batch_69f7a8d219f8819081dc4ce3c83ca0cb`	completed	May 3, 2026, 7:58 p.m.
PDg	Predicate description generation	`batch_69f7aa6795f481908940838ee7041ff5`	completed	May 3, 2026, 8:04 p.m.

Created at: May 3, 2026, 4:05 p.m.