Triple
T17107690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | باي تونس |
E415142
|
entity |
| Predicate | يمنحاللقبمن |
P125962
|
FINISHED |
| Object | السلطان العثماني في البداية |
—
|
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: السلطان العثماني في البداية | Statement: [باي تونس, يمنحاللقبمن, السلطان العثماني في البداية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يمنحاللقبمن Context triple: [باي تونس, يمنحاللقبمن, السلطان العثماني في البداية]
-
A.
awardedFrom
Indicates that one entity has received an award, prize, or honor that originates from or is granted by another entity.
-
B.
isOftenAwardedTo
Indicates that something is frequently given as an award or honor to a particular recipient.
-
C.
授与される勲章
Indicates the relationship in which a medal or decoration is conferred or awarded to someone.
-
D.
awardTo
Indicates that an award, prize, or honor is given or assigned to a particular recipient.
-
E.
awardSymbol
Indicates that one entity serves as the symbolic representation or emblem associated with a particular award given to 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc280b0c8190b9e620b90e0d4b40 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.