Triple
T8859585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ol Chiki script |
E210851
|
entity |
| Predicate | hasDistinctConsonantLetters |
P15734
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ol Chiki script, hasDistinctConsonantLetters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctConsonantLetters Context triple: [Ol Chiki script, hasDistinctConsonantLetters, true]
-
A.
hasDistinctVowelLetters
Indicates that the subject contains vowel letters that are all different from one another, with no vowel repeated.
-
B.
hasNumberOfConsonantLetters
Indicates the relationship between an entity and the count of consonant letters present in its written form.
-
C.
hasDistinctLettersFor
Indicates that one entity is associated with another such that the letters used in the first are all different from (i.e., share no letters with) those used in the second.
-
D.
hasDistinctLetters
chosen
Indicates that all letters in the given string or word are unique, with no character repeated.
-
E.
hasConsonantPhonemes
Indicates that an entity possesses or includes one or more consonant phonemes in its phonological system.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e712d08190bfb1c4ba3acaea90 |
completed | April 1, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69cc5c279ea481908c71756f694b66bf |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:50 p.m.