Triple
T5755438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuang language |
E126954
|
entity |
| Predicate | usesLatinAlphabetSince |
P66193
|
FINISHED |
| Object | 1950s |
—
|
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: 1950s | Statement: [Zhuang language, usesLatinAlphabetSince, 1950s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLatinAlphabetSince Context triple: [Zhuang language, usesLatinAlphabetSince, 1950s]
-
A.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
B.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
C.
ISOBasicLatinDerivative
Indicates that one entity is a derivative or variant form of another entity within the ISO Basic Latin character set.
-
D.
hasCyrillicAlphabetForm
Indicates that an entity has a corresponding representation or form written in the Cyrillic alphabet.
-
E.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02906848c8190bf7b0d62f57c27fa |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021cc68648190bb86d049ebe80f12 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c028fec2bc819083f5dca6a8d9d435 |
completed | March 22, 2026, 5:38 p.m. |
Created at: March 22, 2026, 3:49 p.m.