Triple

T25072375
Position Surface form Disambiguated ID Type / Status
Subject Aquebogue, New York E627949 entity
Predicate postalService P14605 FINISHED
Object Aquebogue Post Office
Aquebogue Post Office is the local United States Postal Service facility serving the hamlet of Aquebogue in Suffolk County, New York.
 E1663852 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: Aquebogue Post Office | Statement: [Aquebogue, New York, postalService, Aquebogue 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: Aquebogue Post Office
Triple: [Aquebogue, New York, postalService, Aquebogue Post Office]
Generated description
Aquebogue Post Office is the local United States Postal Service facility serving the hamlet of Aquebogue in Suffolk County, New York.

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_69e2ff2d71dc8190b4758e57d643cbe4 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f45d15ff608190b0e2b223c82d20e7 completed May 1, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048dc588c819094702d2468ca7f44 completed May 22, 2026, 12:15 p.m.
NEDg Description generation batch_6a104c591a848190b0b2277baf8088e3 completed May 22, 2026, 12:30 p.m.
NED2 Entity disambiguation (via description) batch_6a104cc33b248190a733b46986c28a6a completed May 22, 2026, 12:32 p.m.
Created at: April 18, 2026, 6:17 a.m.