Triple
T31251045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhenyuan |
E796816
|
entity |
| Predicate | usedForDatingDocuments |
P91687
|
FINISHED |
| Object | imperial edicts |
—
|
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: imperial edicts | Statement: [Zhenyuan, usedForDatingDocuments, imperial edicts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForDatingDocuments Context triple: [Zhenyuan, usedForDatingDocuments, imperial edicts]
-
A.
usedForDating
Indicates a relationship where one entity is used as a means, tool, or context for engaging in romantic or dating activities with another entity.
-
B.
usedDocument
Indicates that one entity has employed, referenced, or otherwise made use of a particular document in performing an action or fulfilling a purpose.
-
C.
usedToDate
Indicates that two entities were previously in a romantic or dating relationship but are no longer together.
-
D.
paleographicalDatingMethod
chosen
Indicates the method used to determine the date of an item based on the analysis of its handwriting or script style.
-
E.
datumUsed
Indicates that a particular piece of data is utilized or referenced in performing an action, process, or relation.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 29, 2026, 9:11 p.m.