Triple
T26724673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English translation of Primo Levi’s "Other People’s Trades" |
E673803
|
entity |
| Predicate | translatorNationality |
P42617
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [English translation of Primo Levi’s "Other People’s Trades", translatorNationality, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: translatorNationality Context triple: [English translation of Primo Levi’s "Other People’s Trades", translatorNationality, British]
-
A.
hasTranslatorNationality
chosen
Indicates that the nationality of the translator of a work or text is a specified country or cultural affiliation.
-
B.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
C.
builderNationality
Indicates the country or national affiliation of the entity that built or constructed another entity.
-
D.
nationalityEquivalent
Indicates that two entities have equivalent or corresponding nationalities, treating them as the same for nationality-based reasoning.
-
E.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 27, 2026, 3:42 a.m.