Triple
T32191568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Goodman |
E822268
|
entity |
| Predicate | workOfFictionOriginCountry |
P36448
|
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: [Les Goodman, workOfFictionOriginCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOfFictionOriginCountry Context triple: [Les Goodman, workOfFictionOriginCountry, United States]
-
A.
literaryOriginCountry
chosen
Indicates the country from which a literary work or literary tradition originally comes.
-
B.
countryOfNotableWork
Indicates the country with which a notable work is primarily associated, such as where it was created, set, or gained its significance.
-
C.
associatedWithCountryInFiction
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
-
D.
writtenInCountry
Indicates that a written work was created, authored, or composed within the geographical boundaries of a specific country.
-
E.
hasLiteraryOriginAuthorNationality
Indicates that the nationality of the author from whom a work or concept originates is being specified.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bacd999081908a22bc7e79c57b97 |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.