Triple

T37959301
Position Surface form Disambiguated ID Type / Status
Subject GMA Network Center E946960 entity
Predicate primaryOccupant P75 FINISHED
Object GMA Entertainment Group
GMA Entertainment Group is the content production arm of the Philippine media company GMA Network, responsible for creating many of the country’s popular television programs and entertainment shows.
E56238 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: GMA Entertainment Group | Statement: [GMA Network Center, primaryOccupant, GMA Entertainment Group]
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: GMA Entertainment Group
Triple: [GMA Network Center, primaryOccupant, GMA Entertainment Group]
Generated description
GMA Entertainment Group is the content production arm of the Philippine media company GMA Network, responsible for creating many of the country’s popular television programs and entertainment shows.

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_69f76ef7062c819091bfacb7e83aa1e0 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbdd625108190aa794f777257b0ee completed May 6, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd40fcbc81908d3743c870e7485c completed June 29, 2026, 5:06 a.m.
NEDg Description generation batch_6a41fe7dea008190bdba31dec4813e69 completed June 29, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_6a41ff38219081908809f9918423dd0b completed June 29, 2026, 5:14 a.m.
Created at: May 3, 2026, 4:20 p.m.