Triple
T33405136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther, Obama’s Anger Translator |
E855416
|
entity |
| Predicate | countryOfOriginShow |
P201463
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Luther, Obama’s Anger Translator, countryOfOriginShow, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginShow Context triple: [Luther, Obama’s Anger Translator, countryOfOriginShow, United States]
-
A.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
B.
composerCountryOfOrigin
Indicates the country from which a composer originally comes or with which they are primarily culturally or nationally associated.
-
C.
organizationCountryOfOrigin
Indicates the country where an organization was originally founded or established.
-
D.
titleOriginCountry
chosen
Indicates the country from which a title (such as a work, publication, or creative piece) originally comes or was first produced.
-
E.
orderCountryOfOrigin
Indicates the country from which an order was originally placed, sourced, or shipped.
- 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_69f3496f04a08190804e56ac5098b8e4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00b03a50a88190bfb95cdcfc6142a2 |
completed | May 10, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_6a00afe55f248190b2cb4c7e62cc3ffc |
completed | May 10, 2026, 4:18 p.m. |
Created at: May 1, 2026, 1:36 a.m.