Triple
T32458333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taichu |
E829491
|
entity |
| Predicate | linkedReforms |
P105600
|
FINISHED |
| Object | standardization of the calendar |
—
|
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: standardization of the calendar | Statement: [Taichu, linkedReforms, standardization of the calendar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedReforms Context triple: [Taichu, linkedReforms, standardization of the calendar]
-
A.
associatedReforms
chosen
Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
-
B.
relatedReforms
Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
-
C.
associatedReform
Indicates a relationship where one entity is linked to, connected with, or involved in a particular reform or set of reforms.
-
D.
reformsBy
Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
-
E.
isPartOfReform
Indicates that an action, measure, or component belongs to, contributes to, or is included within a broader reform initiative or process.
- 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_69f3491df9288190afc0b23b1d6e72ce |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: May 1, 2026, 12:56 a.m.