Triple

T30467170
Position Surface form Disambiguated ID Type / Status
Subject Deal Borough Council E775177 entity
Predicate governs P760 FINISHED
Object Borough of Deal, New Jersey
Borough of Deal, New Jersey is a small, affluent seaside community in Monmouth County known for its beaches, historic summer homes, and large seasonal population.
E1918162 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: Borough of Deal, New Jersey | Statement: [Deal Borough Council, governs, Borough of Deal, 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: Borough of Deal, New Jersey
Triple: [Deal Borough Council, governs, Borough of Deal, New Jersey]
Generated description
Borough of Deal, New Jersey is a small, affluent seaside community in Monmouth County known for its beaches, historic summer homes, and large seasonal population.

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_69f2249622a48190b1fae2e3e4ee958a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f686f4d5c48190b3d9430466d3e3ff completed May 2, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27ac1b4aec81909c5def9f0cc04cc7 completed June 9, 2026, 6 a.m.
NEDg Description generation batch_6a27acef0d7481908899cea092a71c89 completed June 9, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a27b605cb7081908d5e7d9110812466 completed June 9, 2026, 6:43 a.m.
Created at: April 29, 2026, 8:11 p.m.