Triple

T27331719
Position Surface form Disambiguated ID Type / Status
Subject Tickfaw River E689818 entity
Predicate hasProtectedArea P855 FINISHED
Object Tickfaw State Park
Tickfaw State Park is a Louisiana state park known for its cypress-tupelo swamps, hardwood forests, and recreational opportunities such as hiking, camping, and wildlife viewing.
E1901897 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: Tickfaw State Park | Statement: [Tickfaw River, hasProtectedArea, Tickfaw 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: Tickfaw State Park
Triple: [Tickfaw River, hasProtectedArea, Tickfaw State Park]
Generated description
Tickfaw State Park is a Louisiana state park known for its cypress-tupelo swamps, hardwood forests, and recreational opportunities such as hiking, camping, and wildlife viewing.

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_69ef355e5b388190a8fc1eba9b4a6656 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62acc15888190ac5be31943518c28 completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274c83027c819094701c4648b45394 completed June 8, 2026, 11:13 p.m.
NEDg Description generation batch_6a274ddf8d688190b480d115456651c3 completed June 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_6a274eb19fd48190a2d38ace0cc22b77 completed June 8, 2026, 11:22 p.m.
Created at: April 27, 2026, 11:38 a.m.