Triple

T27338352
Position Surface form Disambiguated ID Type / Status
Subject Ubon Ratchathani E690019 entity
Predicate hasReligiousSite P916 FINISHED
Object Wat Ban Na Kham Noi
Wat Ban Na Kham Noi is a Buddhist temple located in Thailand’s Ubon Ratchathani Province, serving as a local center for religious practice and community activities.
 E1775956 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: Wat Ban Na Kham Noi | Statement: [Ubon Ratchathani, hasReligiousSite, Wat Ban Na Kham Noi]
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: Wat Ban Na Kham Noi
Triple: [Ubon Ratchathani, hasReligiousSite, Wat Ban Na Kham Noi]
Generated description
Wat Ban Na Kham Noi is a Buddhist temple located in Thailand’s Ubon Ratchathani Province, serving as a local center for religious practice and community activities.

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_69f62ad0b7b88190a69f8e8b2fc9fe3e completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbc7a92081909f92d973743c8a24 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bd4dacfc81908c61517b7286c35d completed May 24, 2026, 8:56 a.m.
NED2 Entity disambiguation (via description) batch_6a12bdeacda08190bfe8354ed2666d23 completed May 24, 2026, 8:59 a.m.
Created at: April 27, 2026, 11:41 a.m.