Triple

T28336868
Position Surface form Disambiguated ID Type / Status
Subject Yingluck Shinawatra E717699 entity
Predicate replacedBy P101 FINISHED
Object Niwatthamrong Boonsongpaisan
Niwatthamrong Boonsongpaisan is a Thai politician who briefly served as acting Prime Minister following the removal of Yingluck Shinawatra.
E1813103 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: Niwatthamrong Boonsongpaisan | Statement: [Yingluck Shinawatra, replacedBy, Niwatthamrong Boonsongpaisan]
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: Niwatthamrong Boonsongpaisan
Triple: [Yingluck Shinawatra, replacedBy, Niwatthamrong Boonsongpaisan]
Generated description
Niwatthamrong Boonsongpaisan is a Thai politician who briefly served as acting Prime Minister following the removal of Yingluck Shinawatra.

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_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bd5c8c08190bd5dea179cf08b35 completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627bac1588190b03fa642ed3b88f1 completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a1628694cf88190a12344a7088c626d completed May 26, 2026, 11:10 p.m.
NED2 Entity disambiguation (via description) batch_6a1628f9ec08819083d6da0fa3836c3a completed May 26, 2026, 11:12 p.m.
Created at: April 28, 2026, 12:36 a.m.