Triple
T9171674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Suzong of Tang |
E220094
|
entity |
| Predicate | eraName |
P2938
|
FINISHED |
| Object |
Shangyuan
Shangyuan was a Chinese imperial era name used during the reign of Emperor Suzong of the Tang dynasty.
|
E784133
|
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: Shangyuan | Statement: [Emperor Suzong of Tang, eraName, Shangyuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shangyuan Context triple: [Emperor Suzong of Tang, eraName, Shangyuan]
-
A.
Da Yuan
Da Yuan is the official Chinese name for the Yuan dynasty, the Mongol-ruled imperial dynasty that governed China from the late 13th to the mid-14th century.
-
B.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
-
C.
Yuncheng
Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
-
D.
Guangyuan
Guangyuan is a prefecture-level city in northern Sichuan, China, known as a regional transport hub with historical and cultural significance along the upper reaches of the Jialing River.
-
E.
Luzhi
Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
- 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: Shangyuan Triple: [Emperor Suzong of Tang, eraName, Shangyuan]
Generated description
Shangyuan was a Chinese imperial era name used during the reign of Emperor Suzong of the Tang dynasty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shangyuan Target entity description: Shangyuan was a Chinese imperial era name used during the reign of Emperor Suzong of the Tang dynasty.
-
A.
Da Yuan
Da Yuan is the official Chinese name for the Yuan dynasty, the Mongol-ruled imperial dynasty that governed China from the late 13th to the mid-14th century.
-
B.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
-
C.
Yuncheng
Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
-
D.
Guangyuan
Guangyuan is a prefecture-level city in northern Sichuan, China, known as a regional transport hub with historical and cultural significance along the upper reaches of the Jialing River.
-
E.
Luzhi
Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaae38ee48190bf783477bc37913d |
completed | April 1, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c077f008190ba1bcd82b3fe9a1d |
completed | April 4, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_69d05cec61908190ae783af982db4170 |
completed | April 4, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d05dbf1ce081908d5c8168a9315942 |
completed | April 4, 2026, 12:39 a.m. |
Created at: March 30, 2026, 7:22 p.m.