Triple

T27410261
Position Surface form Disambiguated ID Type / Status
Subject East 143rd Street–St. Mary’s Street E692123 entity
Predicate hasExitTo P29827 FINISHED
Object St. Mary’s Street
St. Mary’s Street is a local street in the Bronx, New York City, serving the Mott Haven area and providing access to nearby residential blocks and St. Mary’s Park.
 E2287104 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: St. Mary’s Street | Statement: [East 143rd Street–St. Mary’s Street, hasExitTo, St. Mary’s Street]
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: St. Mary’s Street
Triple: [East 143rd Street–St. Mary’s Street, hasExitTo, St. Mary’s Street]
Generated description
St. Mary’s Street is a local street in the Bronx, New York City, serving the Mott Haven area and providing access to nearby residential blocks and St. Mary’s Park.

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_69ef5205fc808190ad3efc5525b8e6d6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cda84c48190bfd814c4ae7a9c60 completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a47606a58348190b5f0f7ea58c99e62 completed July 3, 2026, 7:10 a.m.
NEDg Description generation batch_6a47613ffb3c81908e07e14c3a80ccb7 completed July 3, 2026, 7:14 a.m.
NED2 Entity disambiguation (via description) batch_6a4761bac97881908bf4eed576628d65 completed July 3, 2026, 7:16 a.m.
Created at: April 27, 2026, 12:32 p.m.