Triple

T26717911
Position Surface form Disambiguated ID Type / Status
Subject Si Racha E673616 entity
Predicate hasNearbyIsland P970 FINISHED
Object Ko Loi
Ko Loi is a small island near Si Racha in Chonburi Province, Thailand, known for its seaside views, temple, and as a gateway to nearby islands.
 E1742013 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: Ko Loi | Statement: [Si Racha, hasNearbyIsland, Ko Loi]
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: Ko Loi
Triple: [Si Racha, hasNearbyIsland, Ko Loi]
Generated description
Ko Loi is a small island near Si Racha in Chonburi Province, Thailand, known for its seaside views, temple, and as a gateway to nearby islands.

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_69eecda481d08190aea69f2f7c745f56 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f617ff3a808190bb5cba40ba93830e completed May 2, 2026, 3:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12093d6cc881909a4060ee3d2d0edd completed May 23, 2026, 8:08 p.m.
NEDg Description generation batch_6a120a2acf54819094d2f16637877bb7 completed May 23, 2026, 8:12 p.m.
NED2 Entity disambiguation (via description) batch_6a120b0591e0819080d57a6f01e4128b completed May 23, 2026, 8:16 p.m.
Created at: April 27, 2026, 3:38 a.m.