Triple
T2815767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Remarkable Journey |
E54281
|
entity |
| Predicate | workSubjectNationality |
P43801
|
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: [My Remarkable Journey, workSubjectNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workSubjectNationality Context triple: [My Remarkable Journey, workSubjectNationality, American]
-
A.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
B.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
C.
operatorNationality
Indicates that an operator has a specific national affiliation or country of origin.
-
D.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
-
E.
motherNationality
Indicates the country or national identity associated with a person's mother.
- F. None of above. chosen
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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ed4ac81909f1ec4a3f7869bc1 |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde0f4c648190b9812e64f30c39da |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 9:59 p.m.