Triple
T4008079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haidian District |
E89575
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Beijing Municipality |
E2312
|
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: Beijing Municipality | Statement: [Haidian District, locatedIn, Beijing Municipality]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beijing Municipality Context triple: [Haidian District, locatedIn, Beijing Municipality]
-
A.
Tianjin
Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
-
B.
Beijing
chosen
Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
-
C.
Tiāntán
Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
-
D.
Zhongdu
Zhongdu was the historical capital city of the Jurchen-led Jin dynasty in northern China, located in what is now part of modern Beijing.
-
E.
Lingang
Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa647f80819081180eb267f1cfcc |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55626f19c8190af4705b1cd3b201d |
completed | March 14, 2026, 12:35 p.m. |
Created at: March 9, 2026, 3:34 p.m.