Triple
T12011971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oyá |
E285923
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Yansan
Yansan is a powerful orisha in Yoruba and Afro-Caribbean religions, associated with winds, storms, and the cemetery, often revered as a fierce warrior and guardian of the dead.
|
E960766
|
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: Yansan | Statement: [Oyá, alsoKnownAs, Yansan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yansan Context triple: [Oyá, alsoKnownAs, Yansan]
-
A.
Yuanxin
Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
-
B.
Yansong
Yansong is the given name of Ma Yansong, a prominent Chinese architect known for his futuristic and organic building designs.
-
C.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
-
D.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
E.
Yongcong
Yongcong was a Qing dynasty imperial prince, one of the sons of the Qianlong Emperor of China.
- 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: Yansan Triple: [Oyá, alsoKnownAs, Yansan]
Generated description
Yansan is a powerful orisha in Yoruba and Afro-Caribbean religions, associated with winds, storms, and the cemetery, often revered as a fierce warrior and guardian of the dead.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yansan Target entity description: Yansan is a powerful orisha in Yoruba and Afro-Caribbean religions, associated with winds, storms, and the cemetery, often revered as a fierce warrior and guardian of the dead.
-
A.
Yuanxin
Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
-
B.
Yansong
Yansong is the given name of Ma Yansong, a prominent Chinese architect known for his futuristic and organic building designs.
-
C.
Dayong
Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
-
D.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
E.
Yongcong
Yongcong was a Qing dynasty imperial prince, one of the sons of the Qianlong Emperor of China.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d32b0608190b261567fbd4f415e |
completed | May 1, 2026, 12:31 p.m. |
| NEDg | Description generation | batch_69f53d8ec5448190b303624887f7fa05 |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f56505c0b481909f9caaf338f73033 |
completed | May 2, 2026, 2:44 a.m. |
Created at: April 8, 2026, 9:46 p.m.