Triple

T25078102
Position Surface form Disambiguated ID Type / Status
Subject Longtan District E628108 entity
Predicate knownFor P22 FINISHED
Object Longtan Lake
Longtan Lake is a scenic reservoir and popular recreational spot in Longtan District, Taoyuan, Taiwan, known for its lakeside parks, temples, and cultural festivals.
E1669437 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: Longtan Lake | Statement: [Longtan District, knownFor, Longtan Lake]
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: Longtan Lake
Triple: [Longtan District, knownFor, Longtan Lake]
Generated description
Longtan Lake is a scenic reservoir and popular recreational spot in Longtan District, Taoyuan, Taiwan, known for its lakeside parks, temples, and cultural festivals.

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_69e2ff2e73f881909992bf3eda5c25cb completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f45d1b9bf081909e1a639b63f13a1b completed May 1, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105ced7a788190a153d9a233c82fbc completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a1060da9fac819094a0cf95e7868580 completed May 22, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a10614d9eac8190b35ab1742d392a10 completed May 22, 2026, 1:59 p.m.
Created at: April 18, 2026, 6:21 a.m.