Triple

T27208805
Position Surface form Disambiguated ID Type / Status
Subject Maine Mendoza E683943 entity
Predicate televisionShow P3279 FINISHED
Object Sunday PinaSaya
Sunday PinaSaya is a Philippine Sunday noontime comedy-variety television show that featured popular GMA Network stars, including Maine Mendoza, in sketch, musical, and game segments.
E1760129 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: Sunday PinaSaya | Statement: [Maine Mendoza, televisionShow, Sunday PinaSaya]
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: Sunday PinaSaya
Triple: [Maine Mendoza, televisionShow, Sunday PinaSaya]
Generated description
Sunday PinaSaya is a Philippine Sunday noontime comedy-variety television show that featured popular GMA Network stars, including Maine Mendoza, in sketch, musical, and game segments.

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_69eefad339a08190aeacb2a198f1a39b completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625e6cd708190aea9dc220df25717 completed May 2, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253a1a57c8190b04539b6762be613 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12553613d48190a33bcab491073bbb completed May 24, 2026, 1:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1255e6bc2c8190bfae189c1010f55f completed May 24, 2026, 1:35 a.m.
Created at: April 27, 2026, 9:38 a.m.