Triple
T18241474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Sack |
E436821
|
entity |
| Predicate | portrayerNationality |
P118462
|
FINISHED |
| Object | American |
—
|
LITERAL FINISHED |
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: American | Statement: [Carl Sack, portrayerNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayerNationality Context triple: [Carl Sack, portrayerNationality, American]
-
A.
portrayerName
Indicates the name of the person who portrays or plays a particular character or role.
-
B.
depictsNationality
Indicates that one entity visually represents or portrays the nationality or national identity of another entity.
-
C.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
D.
describesNationality
Indicates that one entity specifies the national identity or citizenship associated with another entity.
-
E.
portrayedByCountryOfCitizenship
chosen
Indicates that the subject is depicted or represented by an individual whose country of citizenship is the specified country.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e387f481909d72574fb7d17923 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:33 a.m.