Triple
T28388933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 南岸区 |
E719096
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
重庆国际会展中心(南坪会展中心)
重庆国际会展中心(南坪会展中心)是位于重庆市南岸区的大型现代化会展与会议综合场馆,常用于举办各类展览、博览会和大型活动。
|
E1816834
|
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: 重庆国际会展中心(南坪会展中心) | Statement: [南岸区, hasLandmark, 重庆国际会展中心(南坪会展中心)]
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: 重庆国际会展中心(南坪会展中心) Triple: [南岸区, hasLandmark, 重庆国际会展中心(南坪会展中心)]
Generated description
重庆国际会展中心(南坪会展中心)是位于重庆市南岸区的大型现代化会展与会议综合场馆,常用于举办各类展览、博览会和大型活动。
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_69eff6ef211081909d31d9be5f5567e6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64ceac7d48190be9d0929bcafd4bb |
completed | May 2, 2026, 7:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a16330676e08190a328a0ca67862381 |
completed | May 26, 2026, 11:55 p.m. |
| NEDg | Description generation | batch_6a1633dd88848190bf73982c2ce00ffd |
completed | May 26, 2026, 11:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a16365587e08190b93663807e950946 |
completed | May 27, 2026, 12:09 a.m. |
Created at: April 28, 2026, 1:12 a.m.