Triple
T16358691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian postage stamps |
E397251
|
entity |
| Predicate | canDepict |
P1581
|
FINISHED |
| Object | Tbilisi landmarks |
—
|
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: Tbilisi landmarks | Statement: [Georgian postage stamps, canDepict, Tbilisi landmarks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canDepict Context triple: [Georgian postage stamps, canDepict, Tbilisi landmarks]
-
A.
canBeDepictedAs
Indicates that one entity is capable of being visually represented or illustrated in the form or style of another entity.
-
B.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
-
C.
depicts
chosen
Indicates that one entity visually represents, portrays, or shows another entity.
-
D.
intendedToDepict
Indicates that one entity was purposefully created or selected in order to visually represent or portray another entity.
-
E.
depictionAction
Indicates an action in which one entity visually represents, illustrates, or portrays another entity.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad1859c819082b47bf9d7fabd9f |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.