Triple

T19182179
Position Surface form Disambiguated ID Type / Status
Subject Hamburg, New Jersey E469601 entity
Predicate adjacentMunicipality P5707 FINISHED
Object Franklin, New Jersey
Franklin, New Jersey is a small borough in Sussex County known historically for its rich zinc mining industry and the famous Franklin mineral deposits.
E2114932 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: Franklin, New Jersey | Statement: [Hamburg, New Jersey, adjacentMunicipality, Franklin, 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: Franklin, New Jersey
Triple: [Hamburg, New Jersey, adjacentMunicipality, Franklin, New Jersey]
Generated description
Franklin, New Jersey is a small borough in Sussex County known historically for its rich zinc mining industry and the famous Franklin mineral deposits.

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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f61cab348190965e96ac0f701f9f completed April 20, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37792448c88190ba18544f9ca011e3 completed June 21, 2026, 5:39 a.m.
NEDg Description generation batch_6a377a6cd7c48190aa8d76a19cd6ef4e completed June 21, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_6a377b124f288190a861cdacfbbc0b5d completed June 21, 2026, 5:48 a.m.
Created at: April 10, 2026, 12:07 p.m.