Triple
T2903443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ties |
E62704
|
entity |
| Predicate | hasTranslatorNationality |
P42617
|
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: [Ties, hasTranslatorNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslatorNationality Context triple: [Ties, hasTranslatorNationality, American]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasNationalityTraditionally
Indicates that an entity is traditionally or historically associated with a particular nationality, regardless of current legal or formal citizenship status.
-
C.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
D.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
E.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0b5546c8190852d9a454e41eee6 |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdd96670c8190b727f9ac27dadf67 |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 10:11 p.m.