Triple

T25428410
Position Surface form Disambiguated ID Type / Status
Subject Taichung City 8th constituency E637182 entity
Predicate partOf P40 FINISHED
Object Taiwan legislative constituencies
Taiwan legislative constituencies are the electoral districts used to elect members to Taiwan’s national legislature, the Legislative Yuan.
E1678664 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: Taiwan legislative constituencies | Statement: [Taichung City 8th constituency, partOf, Taiwan legislative constituencies]
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: Taiwan legislative constituencies
Triple: [Taichung City 8th constituency, partOf, Taiwan legislative constituencies]
Generated description
Taiwan legislative constituencies are the electoral districts used to elect members to Taiwan’s national legislature, the Legislative Yuan.

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_69e75db58a1c8190891b9ff7c2f8414e completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f6c1760c8190a1ba2048804fb379 completed May 2, 2026, 1:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10899e3b948190896e57566bdc228f completed May 22, 2026, 4:51 p.m.
NEDg Description generation batch_6a108a0af25481909d520360b86ff170 completed May 22, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_6a108b00aee0819088928d399c5e52b7 completed May 22, 2026, 4:57 p.m.
Created at: April 21, 2026, 1:58 p.m.