Triple

T27193940
Position Surface form Disambiguated ID Type / Status
Subject Judy Ann Santos-Agoncillo E683546 entity
Predicate notableWork P4 FINISHED
Object Judy Ann’s Kitchen
Judy Ann’s Kitchen is a Filipino cooking show and brand by actress Judy Ann Santos-Agoncillo, featuring home-style recipes and kitchen tips.
 E1760407 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: Judy Ann’s Kitchen | Statement: [Judy Ann Santos-Agoncillo, notableWork, Judy Ann’s Kitchen]
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: Judy Ann’s Kitchen
Triple: [Judy Ann Santos-Agoncillo, notableWork, Judy Ann’s Kitchen]
Generated description
Judy Ann’s Kitchen is a Filipino cooking show and brand by actress Judy Ann Santos-Agoncillo, featuring home-style recipes and kitchen tips.

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_69eefad1fd5c8190a4a46ea6afe58bfa completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625aebd0081908349ebb1e7f380e9 completed May 2, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a125397ac208190bf52c1a8c4e1c425 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a125455f8fc81909ae39b6651a0fdb0 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a125512eb608190b958f82af3475535 completed May 24, 2026, 1:32 a.m.
Created at: April 27, 2026, 9:33 a.m.