Triple
T27609709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soyuz TM-7 |
E700279
|
entity |
| Predicate | visitingNationality |
P163298
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Soyuz TM-7, visitingNationality, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitingNationality Context triple: [Soyuz TM-7, visitingNationality, French]
-
A.
commonVisitorNationalities
Indicates that the related entity has visitors whose nationalities are commonly represented among its overall visitor population.
-
B.
hostNationality
Indicates the national affiliation or citizenship of the host in a given hosting relationship or context.
-
C.
userNationality
Indicates that a user has a specific national affiliation or citizenship.
-
D.
recipientNationality
Indicates that the recipient in a relationship or transaction has a specified national affiliation or citizenship.
-
E.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
- 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_69ef6a4e2e208190b63b7268f405785c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6369a22688190a5674191c90a5d12 |
completed | May 2, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6359d46b88190922dd7de508e3b0e |
completed | May 2, 2026, 5:34 p.m. |
Created at: April 27, 2026, 2:10 p.m.