Triple

T32331587
Position Surface form Disambiguated ID Type / Status
Subject Paco, Manila E826066 entity
Predicate hasLandmark P105 FINISHED
Object San Fernando de Dilao Parish Church
San Fernando de Dilao Parish Church is a historic Catholic church and prominent religious landmark located in the Paco district of Manila, Philippines.
E2010482 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: San Fernando de Dilao Parish Church | Statement: [Paco, Manila, hasLandmark, San Fernando de Dilao Parish Church]
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: San Fernando de Dilao Parish Church
Triple: [Paco, Manila, hasLandmark, San Fernando de Dilao Parish Church]
Generated description
San Fernando de Dilao Parish Church is a historic Catholic church and prominent religious landmark located in the Paco district of Manila, Philippines.

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_69f34913d9048190befaa634025232be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bdefcae881909a82562a56549042 completed May 3, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34703fcd148190b105a710b1a276b5 completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a3471350ec08190ae5394b2a8028840 completed June 18, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a3471ce69508190bbd47938ea429317 completed June 18, 2026, 10:31 p.m.
Created at: May 1, 2026, 12:47 a.m.