Triple

T24640597
Position Surface form Disambiguated ID Type / Status
Subject Long Branch Lake E609948 entity
Predicate hasPart P35 FINISHED
Object Long Branch State Park
Long Branch State Park is a public recreation area in Missouri known for its lakeside camping, boating, fishing, and swimming opportunities around Long Branch Lake.
E1648503 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: Long Branch State Park | Statement: [Long Branch Lake, hasPart, Long Branch State Park]
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: Long Branch State Park
Triple: [Long Branch Lake, hasPart, Long Branch State Park]
Generated description
Long Branch State Park is a public recreation area in Missouri known for its lakeside camping, boating, fishing, and swimming opportunities around Long Branch Lake.

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_69e2c4d28f848190ac38c400060e943d completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2afe7e66c81908c8c5fef152195a0 completed April 30, 2026, 1:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a100ff2ef4c8190b714ed799d19c515 completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a10136992b481909ee04d5c09867f21 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10140b2fec8190aa6d805f54926b56 completed May 22, 2026, 8:30 a.m.
Created at: April 18, 2026, 2:33 a.m.