Triple
T4949131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guo |
E111124
|
entity |
| Predicate | frequencyInChina |
P37986
|
FINISHED |
| Object | common |
—
|
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: common | Statement: [Guo, frequencyInChina, common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyInChina Context triple: [Guo, frequencyInChina, common]
-
A.
frequencyInUS
Indicates how often something occurs, appears, or is used within the United States.
-
B.
frequencyRegion
Indicates that something is associated with, occurs within, or is characterized by a particular range or band of frequencies.
-
C.
frequencyCategory
chosen
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
D.
frequency
Indicates how often an event, action, or relationship occurs within a given period or context.
-
E.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7166bb6c8190a40775ac8bb723a8 |
completed | March 20, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.