Triple
T23250906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany’s Next Topmodel |
E581727
|
entity |
| Predicate | hasInternationalDestinations |
P151540
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Germany’s Next Topmodel, hasInternationalDestinations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalDestinations Context triple: [Germany’s Next Topmodel, hasInternationalDestinations, true]
-
A.
hasInternationalDestinationType
Indicates that something is associated with a type or category of international destination.
-
B.
hasInternationalFlights
Indicates that an airport or airline operates flights connecting to destinations in other countries.
-
C.
internationalDestinationsInclude
Indicates that a given entity’s set of international destinations contains or covers the specified destination(s).
-
D.
hasInternationalTerminal
Indicates that a transportation facility includes a terminal specifically designated for handling international arrivals and departures.
-
E.
hasInternationalPort
Indicates that an entity possesses a port facility that supports international transportation or trade connections.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f5aa9081909775fb7f7dc660b3 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:10 p.m.