Triple
T34909477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregory Corso bibliography |
E1006823
|
entity |
| Predicate | countryOfOriginOfSubject |
P26
|
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: [Gregory Corso bibliography, countryOfOriginOfSubject, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginOfSubject Context triple: [Gregory Corso bibliography, countryOfOriginOfSubject, United States]
-
A.
countryOfOrigin
chosen
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
B.
speciesOrigin
Indicates the place, environment, or source from which a species originally arose or evolved.
-
C.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
-
D.
laterCountryOfOrigin
Indicates that an entity’s country of origin changed, and this predicate specifies the country that became its origin at a later time than a previously associated country.
-
E.
organizationCountryOfOrigin
Indicates the country where an organization was originally founded or established.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a019037edbc8190bdaec436ac2fcec6 |
completed | May 11, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_6a018fe05a34819080068f588b5ff80c |
completed | May 11, 2026, 8:14 a.m. |
Created at: May 3, 2026, 4 p.m.