Triple
T23280006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puyuma language |
E588831
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Peinan
Peinan is an alternative name for the Puyuma language, an Austronesian language spoken by the Puyuma Indigenous people of southeastern Taiwan.
|
E1578306
|
NE FINISHED |
How this triple was built (4 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: Peinan | Statement: [Puyuma language, hasAlternativeName, Peinan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peinan Context triple: [Puyuma language, hasAlternativeName, Peinan]
-
A.
Nan-Shan
Nan-Shan is the fictional steamship featured in Joseph Conrad’s short story “Typhoon,” on which the central storm-tossed voyage takes place.
-
B.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
-
C.
Shifen
Shifen is a historic town in Taiwan’s Pingxi District, best known for its old railway line, sky lantern traditions, and proximity to scenic waterfalls and natural landscapes.
-
D.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
E.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Peinan Triple: [Puyuma language, hasAlternativeName, Peinan]
Generated description
Peinan is an alternative name for the Puyuma language, an Austronesian language spoken by the Puyuma Indigenous people of southeastern Taiwan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peinan Target entity description: Peinan is an alternative name for the Puyuma language, an Austronesian language spoken by the Puyuma Indigenous people of southeastern Taiwan.
-
A.
Nan-Shan
Nan-Shan is the fictional steamship featured in Joseph Conrad’s short story “Typhoon,” on which the central storm-tossed voyage takes place.
-
B.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
-
C.
Shifen
Shifen is a historic town in Taiwan’s Pingxi District, best known for its old railway line, sky lantern traditions, and proximity to scenic waterfalls and natural landscapes.
-
D.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
E.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
- F. None of above. chosen
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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196419eac819081d0beb5767046dc |
completed | April 29, 2026, 5:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f7d1df88190bb71f663d677787f |
completed | May 19, 2026, 10:46 a.m. |
| NEDg | Description generation | batch_6a0c402a5c748190be65373058a7c0a1 |
completed | May 19, 2026, 10:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c4095db6c81908d3186953ac7aa40 |
completed | May 19, 2026, 10:51 a.m. |
Created at: April 17, 2026, 4:50 p.m.