Triple
T8919177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rauschenberg Overseas Culture Interchange |
E212367
|
entity |
| Predicate | numberOfCountriesVisited |
P86406
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Rauschenberg Overseas Culture Interchange, numberOfCountriesVisited, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesVisited Context triple: [Rauschenberg Overseas Culture Interchange, numberOfCountriesVisited, 11]
-
A.
visitedCountry
Indicates that an entity has traveled to and spent time in a particular country.
-
B.
oftenTravelsTo
Indicates that one entity frequently goes to or visits another location or entity.
-
C.
visitedContinent
Indicates that an entity has traveled to and spent time on a particular continent.
-
D.
timeInCountry
Indicates the duration or amount of time that an entity spends or has spent within a particular country.
-
E.
voyagesCompleted
Indicates that an entity has successfully finished one or more journeys or trips from departure to return.
- 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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6613639881909090d060f388a865 |
completed | April 1, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc600a59708190ae426044bbcd7929 |
completed | April 1, 2026, midnight |
Created at: March 30, 2026, 6:56 p.m.