Triple
T14486772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongle Encyclopedia |
E359248
|
entity |
| Predicate | estimatedTotalCharacters |
P32078
|
FINISHED |
| Object | over 370 million |
—
|
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: over 370 million | Statement: [Yongle Encyclopedia, estimatedTotalCharacters, over 370 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedTotalCharacters Context triple: [Yongle Encyclopedia, estimatedTotalCharacters, over 370 million]
-
A.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
-
B.
numberOfCharacters
chosen
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
C.
totalCharactersInStandard
Indicates the total number of characters defined within a given standard or specification.
-
D.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
E.
totalCharactersAfterRelease
Indicates the total number of characters that exist in a work or product after its release (including any additions or updates made post-launch).
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.