Triple
T1948195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiang Chinese |
E42101
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object |
New Xiang
New Xiang is a modern branch of the Xiang group of Chinese dialects, spoken primarily in parts of Hunan province and influenced by neighboring Mandarin varieties.
|
E218214
|
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: New Xiang | Statement: [Xiang Chinese, hasDialects, New Xiang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New Xiang Context triple: [Xiang Chinese, hasDialects, New Xiang]
-
A.
Ximending
Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
-
B.
Xiang
Xiang is the standard abbreviation and common short name used to refer to China’s Hunan Province.
-
C.
Ban Shu Legend
Ban Shu Legend is a Chinese historical romance television drama series centered on the life and adventures of a spirited young woman in the Han dynasty.
-
D.
Vista Chinesa
Vista Chinesa is a famous hilltop lookout in Rio de Janeiro offering panoramic views of the city, beaches, and surrounding rainforest.
-
E.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
- 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: New Xiang Triple: [Xiang Chinese, hasDialects, New Xiang]
Generated description
New Xiang is a modern branch of the Xiang group of Chinese dialects, spoken primarily in parts of Hunan province and influenced by neighboring Mandarin varieties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: New Xiang Target entity description: New Xiang is a modern branch of the Xiang group of Chinese dialects, spoken primarily in parts of Hunan province and influenced by neighboring Mandarin varieties.
-
A.
Ximending
Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
-
B.
Xiang
Xiang is the standard abbreviation and common short name used to refer to China’s Hunan Province.
-
C.
Ban Shu Legend
Ban Shu Legend is a Chinese historical romance television drama series centered on the life and adventures of a spirited young woman in the Han dynasty.
-
D.
Vista Chinesa
Vista Chinesa is a famous hilltop lookout in Rio de Janeiro offering panoramic views of the city, beaches, and surrounding rainforest.
-
E.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb33040c881908f42e80cbe1b1aca |
completed | March 7, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbbf724081909b24680d483edbd1 |
completed | March 8, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69adfc6aa96c81909ae3cff6c7ab7f79 |
completed | March 8, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adfcebbc808190a74f9082636bce11 |
completed | March 8, 2026, 10:49 p.m. |
Created at: March 4, 2026, 7:36 p.m.