Triple
T21484787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luna |
E530088
|
entity |
| Predicate | possibleToponymicOrigin |
P97773
|
FINISHED |
| Object | from places named Luna in Spain |
—
|
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: from places named Luna in Spain | Statement: [Luna, possibleToponymicOrigin, from places named Luna in Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleToponymicOrigin Context triple: [Luna, possibleToponymicOrigin, from places named Luna in Spain]
-
A.
hasEthnolinguisticOriginOfToponym
Indicates that a toponym (place name) originates from or is derived from a particular ethnolinguistic group or language.
-
B.
hasOriginToponym
chosen
Indicates that something originates from, or is derived from, the place denoted by a specific toponym (geographical name).
-
C.
possibleNameEtymology
Indicates a hypothesized or suggested origin or derivation of an entity’s name from another term, source, or linguistic root.
-
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.
hasCountryOfOriginToponym
Indicates that something has a place name (toponym) specifying the country from which it originates.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea365a8481909635f614b23e751f |
completed | April 23, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:21 p.m.