Triple
T30151009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanyang (Southern Ocean) concept in late Qing China |
E766393
|
entity |
| Predicate | linkedToPortCity |
P2745
|
FINISHED |
| Object | Guangzhou |
—
|
NE NERFINISHED |
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: Guangzhou | Statement: [Nanyang (Southern Ocean) concept in late Qing China, linkedToPortCity, Guangzhou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToPortCity Context triple: [Nanyang (Southern Ocean) concept in late Qing China, linkedToPortCity, Guangzhou]
-
A.
hasPortCity
chosen
Indicates that a place or region possesses or is associated with a city that functions as its port.
-
B.
linkedToInlandPort
Indicates a relationship where something has a direct connection or association with an inland port, such as for transport, logistics, or access purposes.
-
C.
isPortOf
Indicates that one location or facility serves as a port or harbor for another place, entity, or transportation route.
-
D.
connectsInlandCityToCoast
Indicates a relationship where a route, link, or infrastructure connects an inland city to a coastal area or city.
-
E.
isPortOfCallFor
Indicates that a location serves as a scheduled stop or destination for a ship, vehicle, or journey.
- F. None of above.
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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 29, 2026, 7:20 p.m.