Triple
T37326948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uncle Bob |
E926630
|
entity |
| Predicate | countryOfCitizenshipOfPortrayer |
P118462
|
FINISHED |
| Object | United States of America |
E14
|
NE 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: United States of America | Statement: [Uncle Bob, countryOfCitizenshipOfPortrayer, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfCitizenshipOfPortrayer Context triple: [Uncle Bob, countryOfCitizenshipOfPortrayer, United States of America]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
portrayedByCountryOfCitizenship
chosen
Indicates that the subject is depicted or represented by an individual whose country of citizenship is the specified country.
-
C.
creatorCountryOfCitizenship
Indicates the country in which the creator holds or held legal citizenship.
-
D.
producerCountryOfCitizenship
Indicates the country in which the producer holds legal citizenship.
-
E.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
- F. None of above.
Provenance (4 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0353887e848190ad98ecbbe7bbc061 |
completed | May 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a406cc9145481909744591e207fd1fb |
completed | June 28, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_6a0352dfb5648190b9f8c9b7c388d2a1 |
completed | May 12, 2026, 4:18 p.m. |
Created at: May 3, 2026, 4:16 p.m.