Triple
T36304484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuang script |
E893906
|
entity |
| Predicate | hasAlphabeticCharacters |
P17387
|
FINISHED |
| Object | consonant letters |
—
|
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: consonant letters | Statement: [Zhuang script, hasAlphabeticCharacters, consonant letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlphabeticCharacters Context triple: [Zhuang script, hasAlphabeticCharacters, consonant letters]
-
A.
hasLowercaseLetters
Indicates that the referenced text contains at least one lowercase alphabetic character.
-
B.
isAlphanumeric
Indicates that a value consists only of alphabetic letters and numeric digits, with no other characters.
-
C.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
D.
hasLetter
chosen
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
E.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
Created at: May 3, 2026, 4:09 p.m.