Triple
T28075558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hán |
E709529
|
entity |
| Predicate | ISO15924TranscriptionOf |
P163447
|
FINISHED |
| Object | Han (Chinese state) |
—
|
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: Han (Chinese state) | Statement: [Hán, ISO15924TranscriptionOf, Han (Chinese state)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISO15924TranscriptionOf Context triple: [Hán, ISO15924TranscriptionOf, Han (Chinese state)]
-
A.
ISO15924Status
Indicates the official status or classification of a script according to the ISO 15924 standard.
-
B.
commonTransliterationSystem
Indicates that two or more written forms are derived using the same standardized system for converting text from one script to another.
-
C.
standardTransliteration
Indicates that one representation of text is a transliteration of another according to a recognized standard or convention.
-
D.
transliterationType
Indicates the specific system or method used to convert text from one writing system into another using corresponding characters.
-
E.
alternativeTransliteration
Indicates that one written form represents an alternative way of transliterating the same original text or name into another script or orthography.
- 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_69ef9b6f8078819098b741274cd1a2ee |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6403f29d481909168f09c19dcbb18 |
completed | May 2, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f637120c008190b2b5adf46f022e48 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f637cad530819086cad3a5ec156013 |
completed | May 2, 2026, 5:43 p.m. |
Created at: April 27, 2026, 8:48 p.m.