Triple
T3461476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongle Emperor |
E73034
|
entity |
| Predicate | numberOfZhengHeVoyagesSponsored |
P46091
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Yongle Emperor, numberOfZhengHeVoyagesSponsored, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfZhengHeVoyagesSponsored Context triple: [Yongle Emperor, numberOfZhengHeVoyagesSponsored, 7]
-
A.
numberOfExpeditions
chosen
Indicates the total count of expeditions associated with a given entity or context.
-
B.
numberOfVoyagesToAmericas
Indicates the count of distinct voyages an entity has made to the Americas.
-
C.
voyagesCompleted
Indicates that an entity has successfully finished one or more journeys or trips from departure to return.
-
D.
purposeOfVoyages
Indicates the intended goals, reasons, or objectives motivating or justifying specific voyages.
-
E.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae745e081909007cd3a664c57f3 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.