Triple

T24729075
Position Surface form Disambiguated ID Type / Status
Subject Telmex E618232 entity
Predicate keyPerson P256 FINISHED
Object Carlos Slim Domit
Carlos Slim Domit is a Mexican businessman and executive, best known as the son of billionaire Carlos Slim Helú and a leading figure in the Slim business empire, particularly in the telecommunications sector.
E1650801 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: Carlos Slim Domit | Statement: [Telmex, keyPerson, Carlos Slim Domit]
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: Carlos Slim Domit
Triple: [Telmex, keyPerson, Carlos Slim Domit]
Generated description
Carlos Slim Domit is a Mexican businessman and executive, best known as the son of billionaire Carlos Slim Helú and a leading figure in the Slim business empire, particularly in the telecommunications sector.

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_69e2fab772608190b74163751047ff50 completed April 18, 2026, 3:29 a.m.
NER Named-entity recognition batch_69f4103385b081909803776101f158b1 completed May 1, 2026, 2:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101bfca6cc8190b376a47624493b12 completed May 22, 2026, 9:03 a.m.
NEDg Description generation batch_6a10248751648190aabfa72ad8ab0b3f completed May 22, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a102586c1288190bf8eeb513537b189 completed May 22, 2026, 9:44 a.m.
Created at: April 18, 2026, 4:01 a.m.