Triple

T25768362
Position Surface form Disambiguated ID Type / Status
Subject Philippine Military Academy E648944 entity
Predicate notableAlumni P51 FINISHED
Object Antonio Trillanes IV
Antonio Trillanes IV is a former Philippine Navy officer and prominent political figure known for leading military uprisings against the Arroyo administration and later serving as a senator.
E1700997 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: Antonio Trillanes IV | Statement: [Philippine Military Academy, notableAlumni, Antonio Trillanes IV]
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: Antonio Trillanes IV
Triple: [Philippine Military Academy, notableAlumni, Antonio Trillanes IV]
Generated description
Antonio Trillanes IV is a former Philippine Navy officer and prominent political figure known for leading military uprisings against the Arroyo administration and later serving as a senator.

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_69e7ab322db0819092d6a2b3d4572e01 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fdf52c2c8190b2354e611031e929 completed May 2, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec9fe54c8190a44fbdb144c063a9 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ee7a469881908be91b7901ada3a2 completed May 23, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_6a10ef6795e08190a1ba5f600628316b completed May 23, 2026, 12:05 a.m.
Created at: April 22, 2026, 5:12 a.m.