Triple
T33131279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changshou |
E847878
|
entity |
| Predicate | usedByRegnalName |
P191370
|
FINISHED |
| Object | Wu Zetian |
—
|
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: Wu Zetian | Statement: [Changshou, usedByRegnalName, Wu Zetian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByRegnalName Context triple: [Changshou, usedByRegnalName, Wu Zetian]
-
A.
tookRegnalName
Indicates that a person adopted and used a specific official regnal name upon assuming a throne or sovereign rulership.
-
B.
usedRegnalNumber
Indicates that an entity (such as a ruler or pope) bore or was designated by a specific regnal number as part of their official title.
-
C.
usedAsRoyalNameOn
Indicates that something served as a royal name or title during a specified time or in a specified context.
-
D.
namedForMonarch
Indicates that one entity bears a name derived from or given in honor of a monarch.
-
E.
eraNameUsedDuringReign
Indicates that a particular era name was officially used throughout the duration of a ruler's reign.
- F. None of above. chosen
Provenance (4 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdf22ab8881908b257f16522920c5 |
completed | May 7, 2026, 6:51 p.m. |
Created at: May 1, 2026, 1:27 a.m.