Triple
T17672392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lydian alphabet |
E440554
|
entity |
| Predicate | hasLetterType |
P128494
|
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: [Lydian alphabet, hasLetterType, consonant letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLetterType Context triple: [Lydian alphabet, hasLetterType, consonant letters]
-
A.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
B.
hasLetterBy
Indicates that an entity possesses or is associated with a letter authored or sent by another entity.
-
C.
hasLetterValue
Indicates that a particular letter or character is associated with a specific numeric or symbolic value.
-
D.
hasLetterDesignation
Indicates that an entity is assigned or associated with a specific letter-based designation or code.
-
E.
hasLettersFor
Indicates that one entity possesses or contains written correspondence intended for another entity.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f69b11c8190b09add33f81776b3 |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10 a.m.