Triple
T2094935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuscany Valley |
E32758
|
entity |
| Predicate | hasFictionalGeographicFeature |
P12436
|
FINISHED |
| Object | vineyard-covered hills |
—
|
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: vineyard-covered hills | Statement: [Tuscany Valley, hasFictionalGeographicFeature, vineyard-covered hills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalGeographicFeature Context triple: [Tuscany Valley, hasFictionalGeographicFeature, vineyard-covered hills]
-
A.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
hasGeographyCharacteristic
chosen
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
C.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
D.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
E.
politicalFeature
Indicates that an entity possesses a political characteristic, attribute, or aspect relevant to governance, power structures, or public policy.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba99ddc48190bb2097b56efb7aca |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b6274081909df36cd7a7c6a675 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.