Triple
T7946020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miao languages |
E184499
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Sichuan |
E38082
|
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: Sichuan | Statement: [Miao languages, spokenIn, Sichuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sichuan Context triple: [Miao languages, spokenIn, Sichuan]
-
A.
Sichuan Province
chosen
Sichuan Province is a populous landlocked region in southwestern China known for its spicy cuisine, rich cultural heritage, and diverse mountainous landscapes including parts of the Tibetan Plateau.
-
B.
Kansu
Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
-
C.
Sichuan Basin
The Sichuan Basin is a large, fertile lowland region in southwestern China, surrounded by mountains and known as a major agricultural and population center.
-
D.
Shíyàn
Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
-
E.
Meizhou
Meizhou is a city in eastern Guangdong, China, known as a cultural and historical center of the Hakka people.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b29a570819091a2ac185a8d57c4 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63ad5fbc819082f7900cd618bd0e |
completed | April 1, 2026, 12:15 a.m. |
Created at: March 30, 2026, 5:09 p.m.