Triple

T28785742
Position Surface form Disambiguated ID Type / Status
Subject Ob Luang National Park E726803 entity
Predicate traversedBy P225 FINISHED
Object Mae Chaem River
The Mae Chaem River is a tributary waterway in northern Thailand that flows through mountainous terrain and scenic protected areas, including Ob Luang National Park.
E1902549 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: Mae Chaem River | Statement: [Ob Luang National Park, traversedBy, Mae Chaem River]
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: Mae Chaem River
Triple: [Ob Luang National Park, traversedBy, Mae Chaem River]
Generated description
The Mae Chaem River is a tributary waterway in northern Thailand that flows through mountainous terrain and scenic protected areas, including Ob Luang National Park.

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_69f0319aabec81908368720196f69a35 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658503a048190b460daa56181dd1e completed May 2, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2757d2ac4c819087ac9bba4ae957fd completed June 9, 2026, 12:01 a.m.
NEDg Description generation batch_6a275a4311f08190b067b8c94e48d019 completed June 9, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a275aeeed3c8190ba20d38ec0af1c74 completed June 9, 2026, 12:14 a.m.
Created at: April 28, 2026, 6:21 a.m.