Triple
T8266591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lycian alphabet |
E193315
|
entity |
| Predicate | hasUniqueCharacters |
P15734
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lycian alphabet, hasUniqueCharacters, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniqueCharacters Context triple: [Lycian alphabet, hasUniqueCharacters, yes]
-
A.
hasDistinctLetters
chosen
Indicates that all letters in the given string or word are unique, with no character repeated.
-
B.
hasDistinctCharacterSet
Indicates that two compared items use different sets of characters, with no character set being a subset or duplicate of the other.
-
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.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
E.
hasDistinctNumerals
Indicates that the numerals in the specified representation are all different from one another, with no digit repeated.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb794e6880819084dff5df42332835 |
completed | March 31, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69cb36b8707881909aca349230495a5a |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:50 p.m.