Triple
T24717269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Paraguay |
E612196
|
entity |
| Predicate | obverseEmblem |
P8603
|
FINISHED |
| Object | national coat of arms of Paraguay |
—
|
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: national coat of arms of Paraguay | Statement: [Flag of Paraguay, obverseEmblem, national coat of arms of Paraguay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: obverseEmblem Context triple: [Flag of Paraguay, obverseEmblem, national coat of arms of Paraguay]
-
A.
obverseDepiction
chosen
Indicates that one entity is depicted on the obverse (front) side of another, such as the front face of a coin or medal.
-
B.
obverseStyle
Indicates the artistic or design style used on the obverse (front) side of an object, such as a coin or medal.
-
C.
obverseText
Indicates the text that appears on the front (obverse) side of an object, typically a coin or medal.
-
D.
obverseOrReverse
Indicates that two sides or aspects of the same object or item are being related as its obverse (front) and reverse (back).
-
E.
obverseHeaddressType
Indicates the type or style of headdress depicted on the obverse (front) side of an object, typically a coin or medal.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:38 a.m.