Triple
T5927111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kunza |
E131839
|
entity |
| Predicate | usedInToponyms |
P20238
|
FINISHED |
| Object | place names in northern Chile |
—
|
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 northern Chile | Statement: [Kunza, usedInToponyms, place names in northern Chile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInToponyms Context triple: [Kunza, usedInToponyms, place names in northern Chile]
-
A.
hasToponymicUse
chosen
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
B.
hasNotableToponym
Indicates that an entity is associated with a place name that is particularly notable, distinctive, or significant.
-
C.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
D.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
E.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.