Triple
T5944443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hui |
E132243
|
entity |
| Predicate | Xiaoerjing |
P66903
|
FINISHED |
| Object | use of Arabic script to write Chinese |
—
|
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: use of Arabic script to write Chinese | Statement: [Hui, Xiaoerjing, use of Arabic script to write Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Xiaoerjing Context triple: [Hui, Xiaoerjing, use of Arabic script to write Chinese]
-
A.
eraAsEmpress
Indicates the time period during which a person held the role or status of empress.
-
B.
מאפיין לוח
Indicates a relationship where something serves as a characteristic, property, or defining feature of a board.
-
C.
eraOfPorcelain
Indicates the historical period or era during which a particular style or type of porcelain was produced or prominent.
-
D.
inker
Indicates that one entity serves as the inker for another, typically applying ink to finalize or enhance an existing drawing or artwork.
-
E.
Inside Out Project
Indicates a relationship where an initiative or action turns internal perspectives, stories, or issues outward into public, visible expression or engagement.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03edf98b881908e9dbc03d3fd6218 |
completed | March 22, 2026, 7:11 p.m. |
Created at: March 22, 2026, 4:01 p.m.