Triple

T31013978
Position Surface form Disambiguated ID Type / Status
Subject Fort Magsaysay E790277 entity
Predicate namedFor P63 FINISHED
Object President Ramon Magsaysay
President Ramon Magsaysay was the seventh President of the Philippines, renowned for his populist leadership style, anti-corruption stance, and strong campaign against the Hukbalahap insurgency in the 1950s.
E1944799 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: President Ramon Magsaysay | Statement: [Fort Magsaysay, namedFor, President Ramon Magsaysay]
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: President Ramon Magsaysay
Triple: [Fort Magsaysay, namedFor, President Ramon Magsaysay]
Generated description
President Ramon Magsaysay was the seventh President of the Philippines, renowned for his populist leadership style, anti-corruption stance, and strong campaign against the Hukbalahap insurgency in the 1950s.

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_69f224c73ca48190a1e46cb58ad4045b completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694890f0c819081d37cedfdb35fba completed May 3, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b0460388190b90337daf8ddb32e completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292c3e3b208190b586c78f19a0fb49 completed June 10, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a292dc95bb8819088c869319844df08 completed June 10, 2026, 9:26 a.m.
Created at: April 29, 2026, 8:57 p.m.