Triple

T38564679
Position Surface form Disambiguated ID Type / Status
Subject Saraburi Province E928181 entity
Predicate hasNationalPark P105 FINISHED
Object Namtok Chet Sao Noi National Park
Namtok Chet Sao Noi National Park is a protected natural area in central Thailand known for its multi-tiered waterfalls, forested landscapes, and popular swimming spots.
E2277195 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: Namtok Chet Sao Noi National Park | Statement: [Saraburi Province, hasNationalPark, Namtok Chet Sao Noi National 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: Namtok Chet Sao Noi National Park
Triple: [Saraburi Province, hasNationalPark, Namtok Chet Sao Noi National Park]
Generated description
Namtok Chet Sao Noi National Park is a protected natural area in central Thailand known for its multi-tiered waterfalls, forested landscapes, and popular swimming spots.

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_69f76eb8d1808190a588af29d8b266d6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9086d50819099f55bc0a56c6293 completed May 7, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ea8ecae88190aeb23a861f3087ab completed June 29, 2026, 3:46 a.m.
NEDg Description generation batch_6a41ee8af66c8190bb634c9b05a5f6ca completed June 29, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_6a41eede3770819090340bca25802273 completed June 29, 2026, 4:04 a.m.
Created at: May 3, 2026, 4:32 p.m.