Triple

T32590613
Position Surface form Disambiguated ID Type / Status
Subject Central Park E833053 entity
Predicate hasFeature P182 FINISHED
Object The Great Hill
The Great Hill is a large, wooded rise in the northwest corner of Central Park that serves as a scenic, elevated lawn and gathering area.
 E2013602 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: The Great Hill | Statement: [Central Park, hasFeature, The Great Hill]
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: The Great Hill
Triple: [Central Park, hasFeature, The Great Hill]
Generated description
The Great Hill is a large, wooded rise in the northwest corner of Central Park that serves as a scenic, elevated lawn and gathering area.

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_69f34929ff648190aded9424aa7564ae completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c690ad9c8190b81204f8bf7adff0 completed May 3, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347baa865481908c792a8fa01b3135 completed June 18, 2026, 11:13 p.m.
NEDg Description generation batch_6a347d37291c81909209d51020e6a749 completed June 18, 2026, 11:20 p.m.
NED2 Entity disambiguation (via description) batch_6a3480fc7ec88190a87901bbb2c0e3af completed June 18, 2026, 11:36 p.m.
Created at: May 1, 2026, 1:05 a.m.