Triple
T1948490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hammer and sickle |
E42107
|
entity |
| Predicate | commonlyDepictedOn |
P34220
|
FINISHED |
| Object | red background |
—
|
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: red background | Statement: [hammer and sickle, commonlyDepictedOn, red background]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyDepictedOn Context triple: [hammer and sickle, commonlyDepictedOn, red background]
-
A.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
B.
depictsName
Indicates that something visually represents or portrays the name of an entity.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
E.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3315df481908f60cd87453fbc03 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff25a588190bb4cbc8df9fc6d64 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:36 p.m.