Triple
T30513753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiangshan |
E776501
|
entity |
| Predicate | historicalCulturalRegion |
P915
|
FINISHED |
| Object | Lingnan |
—
|
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: Lingnan | Statement: [Xiangshan, historicalCulturalRegion, Lingnan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalCulturalRegion Context triple: [Xiangshan, historicalCulturalRegion, Lingnan]
-
A.
historicalRegion
chosen
Indicates that an entity is or was a geographically defined area recognized for its significance during a particular historical period.
-
B.
historicallyImportantRegion
Indicates that a region holds significant importance due to its impact on historical events, developments, or cultural heritage.
-
C.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
D.
historicalRegionOfInfluence
Indicates that one entity was historically within the geographic, political, or cultural sphere of influence of another entity.
-
E.
regionHasCulturalHeritage
Indicates that a specific region possesses, contains, or is associated with particular cultural heritage.
- 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_69f2249a155c8190b1d512106007e9bb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fef5cf8da881908260ec633830375d |
completed | May 9, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69fef455e40481909861c82007b79bc0 |
completed | May 9, 2026, 8:46 a.m. |
Created at: April 29, 2026, 8:16 p.m.