Triple
T20925796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Donna |
E515339
|
entity |
| Predicate | firstPopularizedInLanguage |
P2352
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Donna Donna, firstPopularizedInLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPopularizedInLanguage Context triple: [Donna Donna, firstPopularizedInLanguage, English]
-
A.
firstAppearanceLanguage
Indicates the language in which an entity (such as a work or character) was first introduced or appeared.
-
B.
popularizedIn
chosen
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
C.
popularizedAfter
Indicates that one entity became widely known, accepted, or influential only after another specified entity had already gained popularity.
-
D.
firstProminentUse
Indicates the earliest notable or widely recognized instance in which something was used in a significant or influential way.
-
E.
languageOfEarliestForm
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f65200b08190ac208204a20f5a6a |
completed | April 21, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:49 p.m.