Triple

T30908694
Position Surface form Disambiguated ID Type / Status
Subject La Cigarra E787375 entity
Predicate notablePerformer P17435 FINISHED
Object Lola Beltrán
Lola Beltrán was a renowned Mexican ranchera singer and actress, celebrated as one of the genre’s greatest interpreters.
E2226731 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: Lola Beltrán | Statement: [La Cigarra, notablePerformer, Lola Beltrán]
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: Lola Beltrán
Triple: [La Cigarra, notablePerformer, Lola Beltrán]
Generated description
Lola Beltrán was a renowned Mexican ranchera singer and actress, celebrated as one of the genre’s greatest interpreters.

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_69f224be300c8190a6513ce1ee0a7026 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692822c48819085dd831574623289 completed May 3, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40822829e881909e53dd7d47d72904 completed June 28, 2026, 2:08 a.m.
NEDg Description generation batch_6a408301ac7481909a67b2b663296357 completed June 28, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_6a4083b93a508190819fe83da97374f7 completed June 28, 2026, 2:15 a.m.
Created at: April 29, 2026, 8:50 p.m.