Triple

T28900901
Position Surface form Disambiguated ID Type / Status
Subject 新竹市 E732946 entity
Predicate hasTouristAttraction P530 FINISHED
Object 新竹市立動物園
新竹市立動物園是位於臺灣新竹市、以小而精緻與親子互動體驗聞名的在地歷史動物園。
 E1838749 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: 新竹市立動物園 | Statement: [新竹市, hasTouristAttraction, 新竹市立動物園]
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: 新竹市立動物園
Triple: [新竹市, hasTouristAttraction, 新竹市立動物園]
Generated description
新竹市立動物園是位於臺灣新竹市、以小而精緻與親子互動體驗聞名的在地歷史動物園。

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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65aa7a3708190997f03877d5a4aa0 completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24d40dd7fc819084422ee3f9b62268 completed June 7, 2026, 2:14 a.m.
NEDg Description generation batch_6a24d8d496948190b0616b14061e9eeb completed June 7, 2026, 2:35 a.m.
NED2 Entity disambiguation (via description) batch_6a24db0dce7c819097bbc57739505752 completed June 7, 2026, 2:44 a.m.
Created at: April 28, 2026, 8:02 a.m.