Triple
T38218584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheingau wine region |
E1010748
|
entity |
| Predicate | famousTown |
P2813
|
FINISHED |
| Object | Rüdesheim am Rhein |
—
|
NE NERFINISHED |
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: Rüdesheim am Rhein | Statement: [Rheingau wine region, famousTown, Rüdesheim am Rhein]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: famousTown Context triple: [Rheingau wine region, famousTown, Rüdesheim am Rhein]
-
A.
notableHumanSettlement
Indicates that a location is recognized as a significant or noteworthy human settlement, such as a city, town, or village.
-
B.
isInTownKnownFor
Indicates that one entity is located in a town that is notable or distinguished for the other entity.
-
C.
hasFamousCity
chosen
Indicates that an entity possesses or is associated with a city that is widely recognized or renowned.
-
D.
popularTown
Indicates that a town is widely liked, frequently visited, or well-regarded by many people.
-
E.
inscriptionFamousFor
Indicates that an inscription is widely recognized or notable specifically because of the referenced feature, event, content, or characteristic.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.