Triple
T24757639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kâte language |
E619334
|
entity |
| Predicate | hasPersonDistinction |
P157709
|
FINISHED |
| Object | third person |
—
|
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: third person | Statement: [Kâte language, hasPersonDistinction, third person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPersonDistinction Context triple: [Kâte language, hasPersonDistinction, third person]
-
A.
hasPersonDistinction
Indicates that a person holds or has been awarded a particular honor, title, or distinction.
-
B.
hasPersonDistinction
Indicates that a person holds or has been granted a particular honor, award, title, or other notable distinction.
-
C.
hasDistinction
Indicates that one entity possesses, is awarded, or is recognized with a special honor, title, or mark of excellence in relation to another entity or context.
-
D.
hasNotableRecognitionFor
Indicates that an entity has received notable recognition, such as awards, honors, or distinctions, specifically for another entity or achievement.
-
E.
nameDistinction
Indicates that two entities are distinguished from one another specifically by differences in their names.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 4:26 a.m.