Triple

T25153074
Position Surface form Disambiguated ID Type / Status
Subject Bass River Township E626231 entity
Predicate adjacentTo P224 FINISHED
Object Woodland Township, New Jersey
Woodland Township, New Jersey is a sparsely populated, heavily forested municipality in Burlington County that lies largely within the New Jersey Pinelands.
E1883891 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: Woodland Township, New Jersey | Statement: [Bass River Township, adjacentTo, Woodland Township, New Jersey]
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: Woodland Township, New Jersey
Triple: [Bass River Township, adjacentTo, Woodland Township, New Jersey]
Generated description
Woodland Township, New Jersey is a sparsely populated, heavily forested municipality in Burlington County that lies largely within the New Jersey Pinelands.

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_69e2ff2834ec8190b0872e2ec3d76023 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f46b84d59881908e038999896aa8f4 completed May 1, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8bf0828819087666607bdca4ab8 completed June 8, 2026, 1:50 p.m.
NEDg Description generation batch_6a26cd2db9bc8190bdbe700f6522ef39 completed June 8, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_6a26d94836a88190bf71dbdf15a26d71 completed June 8, 2026, 3:01 p.m.
Created at: April 18, 2026, 6:30 a.m.