Triple
T3298869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geʽez script |
E69281
|
entity |
| Predicate | hasBaseConsonantCount |
P4431
|
FINISHED |
| Object | 26 |
—
|
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: 26 | Statement: [Geʽez script, hasBaseConsonantCount, 26]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaseConsonantCount Context triple: [Geʽez script, hasBaseConsonantCount, 26]
-
A.
hasNumberOfConsonantLetters
chosen
Indicates the relationship between an entity and the count of consonant letters present in its written form.
-
B.
hasConsonantPhonemes
Indicates that an entity possesses or includes one or more consonant phonemes in its phonological system.
-
C.
hasConsonantClusters
Indicates that the subject contains sequences of two or more consonants occurring together without intervening vowels.
-
D.
hasConsonantSigns
Indicates that one entity possesses or includes consonant sign characters as part of its representation or structure.
-
E.
hasConsonantLengthContrast
Indicates that a language distinguishes meaning between words based on differences in the length or duration of consonant sounds.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a49b748190b6db99a85c3cb3c5 |
completed | March 8, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69ada42407dc81909f60d7a14e1b7934 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.