Triple

T29392876
Position Surface form Disambiguated ID Type / Status
Subject Liwasang Bonifacio area E745415 entity
Predicate adjacentTo P224 FINISHED
Object Manila Central Post Office
Manila Central Post Office is a historic neoclassical landmark in Manila that long served as the Philippines’ primary postal hub and an iconic riverside civic building.
E1867240 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: Manila Central Post Office | Statement: [Liwasang Bonifacio area, adjacentTo, Manila Central Post Office]
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: Manila Central Post Office
Triple: [Liwasang Bonifacio area, adjacentTo, Manila Central Post Office]
Generated description
Manila Central Post Office is a historic neoclassical landmark in Manila that long served as the Philippines’ primary postal hub and an iconic riverside civic building.

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_69f0a79dfabc81908755382ee47791e2 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f669fff6488190ae591e1c99dfeed8 completed May 2, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d9149104819096d0bb4c34a31f4f completed June 7, 2026, 8:48 p.m.
NEDg Description generation batch_6a25dd504b8881908cfcc47c644035ba completed June 7, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_6a25e22054d081908784600599c12ed5 completed June 7, 2026, 9:26 p.m.
Created at: April 28, 2026, 2:43 p.m.