Triple
T22371656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fassan Ladin |
E553053
|
entity |
| Predicate | usedInToponymy |
P20238
|
FINISHED |
| Object | place names in Val di Fassa |
—
|
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: place names in Val di Fassa | Statement: [Fassan Ladin, usedInToponymy, place names in Val di Fassa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInToponymy Context triple: [Fassan Ladin, usedInToponymy, place names in Val di Fassa]
-
A.
usedAsToponymicBy
Indicates that one entity is employed as a place-based surname or name-forming element for another entity.
-
B.
hasToponymicUse
chosen
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
C.
usedAsToponymUntil
Indicates that a name or term functioned as a place name (toponym) for a location up to a specified end time or period.
-
D.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
E.
influenceOnToponymy
Indicates that one entity has affected or shaped the naming, form, or development of place names associated with another entity.
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15804f1b08190b57689e6afb615a0 |
completed | April 29, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69e73011e6388190a05edf137f488441 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:44 p.m.