Triple

T23579700
Position Surface form Disambiguated ID Type / Status
Subject Ringwood, New Jersey E582163 entity
Predicate hasHistoricCommunity P11485 FINISHED
Object Erskine Lakes community
Erskine Lakes community is a historic residential lake community in Ringwood, New Jersey, known for its scenic setting and recreational waterfront lifestyle.
E1594916 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: Erskine Lakes community | Statement: [Ringwood, New Jersey, hasHistoricCommunity, Erskine Lakes community]
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: Erskine Lakes community
Triple: [Ringwood, New Jersey, hasHistoricCommunity, Erskine Lakes community]
Generated description
Erskine Lakes community is a historic residential lake community in Ringwood, New Jersey, known for its scenic setting and recreational waterfront lifestyle.

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_69e248f8d8248190acd5aee77f0d1709 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1afd8e5ec81909fbdcf68bc14078e completed April 29, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f4572ad7c8190879c962e97c156ec completed May 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a0f46faaa5481909c99edb4bdd30049 completed May 21, 2026, 5:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f484988d081909280fe863dc80e30 completed May 21, 2026, 6 p.m.
Created at: April 17, 2026, 6:39 p.m.