Triple
T9252793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chen-Xu dialect group |
E222364
|
entity |
| Predicate | hasVarietyType |
P64735
|
FINISHED |
| Object | Chinese dialect |
—
|
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: Chinese dialect | Statement: [Chen-Xu dialect group, hasVarietyType, Chinese dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVarietyType Context triple: [Chen-Xu dialect group, hasVarietyType, Chinese dialect]
-
A.
hasVariabilityType
chosen
Indicates that an entity is associated with a specific kind or category of variability (e.g., how or in what way it varies).
-
B.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
C.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
hasNumberOfTypes
Indicates that an entity is associated with a specific count of distinct types or categories it possesses or includes.
-
E.
hasGMVarieties
Indicates that an entity possesses or includes one or more genetically modified (GM) varieties.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b0789481908e8e44ebf1b3c713 |
completed | April 1, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:31 p.m.