Triple
T10035427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 沙面岛 |
E204952
|
entity |
| Predicate | 历史角色 |
P87512
|
FINISHED |
| Object | 广州重要对外通商口岸区域 |
—
|
LITERAL 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: 广州重要对外通商口岸区域 | Statement: [沙面岛, 历史角色, 广州重要对外通商口岸区域]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 历史角色 Context triple: [沙面岛, 历史角色, 广州重要对外通商口岸区域]
-
A.
historicalFigure
Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
-
B.
roleInHumanHistory
chosen
Indicates the function, influence, or significance that an entity has had within the course of human history.
-
C.
historicalPeople
Indicates that the related entities are people who lived in or are associated with a past historical period or context.
-
D.
usesRealHistoricalFigures
Indicates that the work includes or depicts actual people from real history rather than entirely fictional characters.
-
E.
historicPlayer
Indicates that an entity is recognized as a notable player from the past, typically associated with historical significance in its domain.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdce4a515c8190baec86d924623b12 |
completed | April 2, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69cd4b8638508190b22acc65500ec7d6 |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:55 p.m.