Triple
T37907945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribbon of Saint George |
E945604
|
entity |
| Predicate | popularizedSince |
P195524
|
FINISHED |
| Object | 2005 |
—
|
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: 2005 | Statement: [Ribbon of Saint George, popularizedSince, 2005]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularizedSince Context triple: [Ribbon of Saint George, popularizedSince, 2005]
-
A.
popularizedAfter
Indicates that one entity became widely known, accepted, or influential only after another specified entity had already gained popularity.
-
B.
popularizedOn
Indicates that something became widely known, accepted, or fashionable through a particular platform, medium, or context.
-
C.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
D.
popularizedBy
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
E.
popularizedInEnglishBy
Indicates that one entity is responsible for making another entity widely known or commonly used within the English language context.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
| PDg | Predicate description generation | batch_69fdd5faea908190a17d77e050362ef5 |
completed | May 8, 2026, 12:24 p.m. |
Created at: May 3, 2026, 4:20 p.m.