Triple

T36509652
Position Surface form Disambiguated ID Type / Status
Subject Mott Haven E899862 entity
Predicate hasHistoricDistrict P295 FINISHED
Object Mott Haven North Historic District
Mott Haven North Historic District is a designated historic area in the South Bronx known for its late-19th- and early-20th-century residential and industrial architecture.
E25074 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: Mott Haven North Historic District | Statement: [Mott Haven, hasHistoricDistrict, Mott Haven North Historic District]
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: Mott Haven North Historic District
Triple: [Mott Haven, hasHistoricDistrict, Mott Haven North Historic District]
Generated description
Mott Haven North Historic District is a designated historic area in the South Bronx known for its late-19th- and early-20th-century residential and industrial architecture.

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_69f76e5dada881909da2d34bc7a9202a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c1edc644819091c04704fb99b5bb completed May 3, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39f900b49c8190bfa9cfe94595216f completed June 23, 2026, 3:09 a.m.
NEDg Description generation batch_6a39fb282f808190b4e43eb479ec1535 completed June 23, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_6a39fdd52f8481908a0a07b68f24e4f0 completed June 23, 2026, 3:30 a.m.
Created at: May 3, 2026, 4:10 p.m.