Triple
T5895772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganjami Odia |
E131096
|
entity |
| Predicate | hasDistinctAccent |
P18160
|
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: [Ganjami Odia, hasDistinctAccent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctAccent Context triple: [Ganjami Odia, hasDistinctAccent, yes]
-
A.
hasAccent
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
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.
hasDistinctFeature
chosen
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
D.
hasDistinctVowelLetters
Indicates that the subject contains vowel letters that are all different from one another, with no vowel repeated.
-
E.
hasDistinctLetters
Indicates that all letters in the given string or word are unique, with no character 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:58 p.m.