Triple
T10985364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bohai Strait |
E259614
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Penglai |
E448644
|
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: Penglai | Statement: [Bohai Strait, nearCity, Penglai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penglai Context triple: [Bohai Strait, nearCity, Penglai]
-
A.
Penglai
chosen
Penglai is a coastal city in northeastern Shandong, China, famed in Chinese mythology and history as a legendary isle of immortals and a scenic seaside destination.
-
B.
Longkou
Longkou is a coastal city in northeastern Shandong Province, China, known for its port, marine-based industries, and production of Longkou vermicelli.
-
C.
Laizhou
Laizhou is a county-level coastal city in northeastern Shandong Province, China, known for its salt, gold, and chemical industries.
-
D.
Kaiping
Kaiping is a county-level city in Guangdong Province, China, known for its distinctive diaolou watchtowers and as part of the Sze Yup region with a strong overseas Chinese heritage.
-
E.
Caishikou
Caishikou is a subway station in central Beijing that serves as an important stop on the city’s urban rail network.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ed1eb88190b7333b746f76a088 |
completed | April 9, 2026, 9:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344d860b08190a035570191c54d7c |
completed | April 18, 2026, 8:46 a.m. |
Created at: April 8, 2026, 9:24 p.m.