Triple

T35989731
Position Surface form Disambiguated ID Type / Status
Subject Telemundo Station Group E1040809 entity
Predicate ownsStationBrand P53258 FINISHED
Object Telemundo Houston
Telemundo Houston is a Spanish-language television station serving the Houston, Texas market, providing local news, entertainment, and Telemundo network programming to Hispanic audiences.
E2164946 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: Telemundo Houston | Statement: [Telemundo Station Group, ownsStationBrand, Telemundo Houston]
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: Telemundo Houston
Triple: [Telemundo Station Group, ownsStationBrand, Telemundo Houston]
Generated description
Telemundo Houston is a Spanish-language television station serving the Houston, Texas market, providing local news, entertainment, and Telemundo network programming to Hispanic audiences.

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_69f76e29084c819083987b828d414de7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b1bdc38c8190aff196b890b45979 completed May 3, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfe824b08190810cff02a3bbe883 completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c0a8a0908190a845f3f6e7040e1e completed June 22, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_6a38c164f0e88190bef255d462f21732 completed June 22, 2026, 5 a.m.
Created at: May 3, 2026, 4:07 p.m.