Triple

T27246864
Position Surface form Disambiguated ID Type / Status
Subject Piolo Pascual E687368 entity
Predicate awardReceived P11 FINISHED
Object PMPC Star Awards for Movies
The PMPC Star Awards for Movies is an annual Philippine film awards ceremony organized by the Philippine Movie Press Club that honors outstanding achievements in the local movie industry.
E1774248 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: PMPC Star Awards for Movies | Statement: [Piolo Pascual, awardReceived, PMPC Star Awards for Movies]
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: PMPC Star Awards for Movies
Triple: [Piolo Pascual, awardReceived, PMPC Star Awards for Movies]
Generated description
The PMPC Star Awards for Movies is an annual Philippine film awards ceremony organized by the Philippine Movie Press Club that honors outstanding achievements in the local movie industry.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626b1c8548190a6a81f6c460aef88 completed May 2, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbc1d16c8190ac37f9e5f7beedab completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bc906eb481908d12f171b1230dbe completed May 24, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd3f12b481908606b8e373ff408a completed May 24, 2026, 8:56 a.m.
Created at: April 27, 2026, 10:42 a.m.