Triple
T22850102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baima language |
E566334
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Baima hua
Baima hua is a Tibeto-Burman language spoken by the Baima people in parts of Sichuan and Gansu provinces in China.
|
E1556661
|
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: Baima hua | Statement: [Baima language, hasAlternativeName, Baima hua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baima hua Context triple: [Baima language, hasAlternativeName, Baima hua]
-
A.
Huay-Huay
Huay-Huay is a town and district-level settlement located in the high Andean region of central Peru.
-
B.
Yulanpen Jing
Yulanpen Jing is a key Mahayana Buddhist scripture that narrates the story of Maudgalyāyana saving his mother from the realm of hungry ghosts and underpins the rituals of the Ullambana (Ghost) Festival.
-
C.
Xuanhu
Xuanhu is the art name of Xu Guangqi, a prominent late Ming dynasty scholar-official, scientist, and collaborator of Matteo Ricci in introducing Western science to China.
-
D.
Hua
Hua is a Chinese given name commonly used for both males and females, often associated with meanings like "flower" or "China."
-
E.
Meidi Dadao
Meidi Dadao is a metro station in Guangzhou, China, serving as a terminus on Guangzhou Metro Line 7.
- 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: Baima hua Triple: [Baima language, hasAlternativeName, Baima hua]
Generated description
Baima hua is a Tibeto-Burman language spoken by the Baima people in parts of Sichuan and Gansu provinces in China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baima hua Target entity description: Baima hua is a Tibeto-Burman language spoken by the Baima people in parts of Sichuan and Gansu provinces in China.
-
A.
Huay-Huay
Huay-Huay is a town and district-level settlement located in the high Andean region of central Peru.
-
B.
Yulanpen Jing
Yulanpen Jing is a key Mahayana Buddhist scripture that narrates the story of Maudgalyāyana saving his mother from the realm of hungry ghosts and underpins the rituals of the Ullambana (Ghost) Festival.
-
C.
Xuanhu
Xuanhu is the art name of Xu Guangqi, a prominent late Ming dynasty scholar-official, scientist, and collaborator of Matteo Ricci in introducing Western science to China.
-
D.
Hua
Hua is a Chinese given name commonly used for both males and females, often associated with meanings like "flower" or "China."
-
E.
Meidi Dadao
Meidi Dadao is a metro station in Guangzhou, China, serving as a terminus on Guangzhou Metro Line 7.
- 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eb74700819090d191b3a7a17034 |
completed | April 29, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba7be4c7c81908ce5d01eb2926aea |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba8bb77bc81909c5422f9d73c1e70 |
completed | May 19, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba94752c48190a8892cac5ef862b2 |
completed | May 19, 2026, 12:05 a.m. |
Created at: April 17, 2026, 3:36 p.m.