Triple
T28659629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eir (Marvel Cinematic Universe) |
E725429
|
entity |
| Predicate | countryOfFirstAppearance |
P111542
|
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: [Eir (Marvel Cinematic Universe), countryOfFirstAppearance, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfFirstAppearance Context triple: [Eir (Marvel Cinematic Universe), countryOfFirstAppearance, United States]
-
A.
countryOfFirstRelease
Indicates the country in which a work (such as a film, game, or product) was first officially released.
-
B.
countryOfFirstEvent
Indicates the country in which the first event in a sequence or series took place.
-
C.
firstAppearanceHostCountry
chosen
Indicates that the referenced country is the one where an entity (such as an event, person, or organization) made its first recorded appearance or debut.
-
D.
placeOfFirstPopularity
Indicates the location where something (such as a work, idea, or person) first gained notable recognition or widespread popularity.
-
E.
televisionDebutCountry
Indicates the country in which a person or work first appeared or was broadcast on television.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
Created at: April 28, 2026, 4:57 a.m.