Triple

T33966272
Position Surface form Disambiguated ID Type / Status
Subject Guillermo Francella E870861 entity
Predicate notableWork P4 FINISHED
Object Casados con hijos
Casados con hijos is an Argentine sitcom, adapted from the American series Married... with Children, that became a popular staple of local television comedy.
 E2075694 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: Casados con hijos | Statement: [Guillermo Francella, notableWork, Casados con hijos]
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: Casados con hijos
Triple: [Guillermo Francella, notableWork, Casados con hijos]
Generated description
Casados con hijos is an Argentine sitcom, adapted from the American series Married... with Children, that became a popular staple of local television comedy.

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_69f3499ce8e88190b66e1d49ad8c7037 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f702db269c8190a1dc02228a67c290 completed May 3, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689ea105c8190a3d17d883c3e0a5b completed June 20, 2026, 12:39 p.m.
NEDg Description generation batch_6a368a8b7c04819093bd8e08512c9062 completed June 20, 2026, 12:41 p.m.
NED2 Entity disambiguation (via description) batch_6a368b9656648190ab445be933b50944 completed June 20, 2026, 12:46 p.m.
Created at: May 1, 2026, 1:50 a.m.