Triple

T26617840
Position Surface form Disambiguated ID Type / Status
Subject Elsa Pataky E668112 entity
Predicate birthName P65 FINISHED
Object Elsa Lafuente Medianu
Elsa Lafuente Medianu, known professionally as Elsa Pataky, is a Spanish actress and model recognized for her roles in the Fast & Furious film franchise and her high-profile marriage to actor Chris Hemsworth.
E1762287 NE 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: Elsa Lafuente Medianu | Statement: [Elsa Pataky, birthName, Elsa Lafuente Medianu]
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: Elsa Lafuente Medianu
Triple: [Elsa Pataky, birthName, Elsa Lafuente Medianu]
Generated description
Elsa Lafuente Medianu, known professionally as Elsa Pataky, is a Spanish actress and model recognized for her roles in the Fast & Furious film franchise and her high-profile marriage to actor Chris Hemsworth.

Provenance (5 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_69ee9cfe16088190a3dddd68e3c7b1ea completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615adea108190900f6809d6cdeb81 completed May 2, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12535a16e48190bdfe798f281fd4ec completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12574c06788190951ce13779ea5ba8 completed May 24, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_6a125793327881908c67b67f1bdf19e6 completed May 24, 2026, 1:42 a.m.
Created at: April 27, 2026, 2:19 a.m.