Triple
T8066437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Han |
E188254
|
entity |
| Predicate | pinyinName |
P9333
|
FINISHED |
| Object |
Hán
Hán is the pinyin transcription of the name of the ancient Chinese State of Han, one of the major states during the Warring States period.
|
E709529
|
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: Hán | Statement: [State of Han, pinyinName, Hán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hán Context triple: [State of Han, pinyinName, Hán]
-
A.
Yunca
Yunca is an alternative name for the extinct Mochica language once spoken on Peru’s northern coast.
-
B.
Tangut
Tangut is an extinct Tibeto-Burman language once used in the Western Xia dynasty, best known today for its large and complex logographic writing system.
-
C.
Zhong Wen
Zhong Wen is the tough, determined police officer portrayed by Jackie Chan in the action film "Police Story 2013."
-
D.
Zhou
Zhou is a common Chinese surname borne by many notable figures in Chinese history and politics.
-
E.
Hakka
Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
- 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: Hán Triple: [State of Han, pinyinName, Hán]
Generated description
Hán is the pinyin transcription of the name of the ancient Chinese State of Han, one of the major states during the Warring States period.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hán Target entity description: Hán is the pinyin transcription of the name of the ancient Chinese State of Han, one of the major states during the Warring States period.
-
A.
Yunca
Yunca is an alternative name for the extinct Mochica language once spoken on Peru’s northern coast.
-
B.
Tangut
Tangut is an extinct Tibeto-Burman language once used in the Western Xia dynasty, best known today for its large and complex logographic writing system.
-
C.
Zhong Wen
Zhong Wen is the tough, determined police officer portrayed by Jackie Chan in the action film "Police Story 2013."
-
D.
Zhou
Zhou is a common Chinese surname borne by many notable figures in Chinese history and politics.
-
E.
Hakka
Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ff75d208190b7c53d2fe55878ac |
completed | March 31, 2026, 3:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63e1ed44819083ed9db6c9d7b0fd |
completed | April 1, 2026, 12:16 a.m. |
| NEDg | Description generation | batch_69cc651c5f788190908c6d84c58cba0f |
completed | April 1, 2026, 12:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc6649d2348190996802140b455348 |
completed | April 1, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:26 p.m.