Triple
T30800113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Lowe |
E784339
|
entity |
| Predicate | countryOfTreatment |
P8559
|
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: [Leonard Lowe, countryOfTreatment, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfTreatment Context triple: [Leonard Lowe, countryOfTreatment, United States]
-
A.
treatmentCountry
chosen
Indicates the country where a treatment, therapy, or medical intervention is administered or takes place.
-
B.
countryOfFacility
Indicates that a facility is located within or belongs to a specific country.
-
C.
treatmentLocation
Indicates the place or facility where a treatment or medical intervention is administered to an entity.
-
D.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
E.
countryOfSubmission
Indicates the country in which something (such as a document, application, or work) is formally submitted.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ffada24d188190a576a02dc280a7fb |
completed | May 9, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69ffad46d6ac819081772f408b1389d5 |
completed | May 9, 2026, 9:55 p.m. |
Created at: April 29, 2026, 8:42 p.m.