Triple
T28918170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melfitani |
E733429
|
entity |
| Predicate | hasGentilicForm |
P180425
|
FINISHED |
| Object | Melfitano |
—
|
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: Melfitano | Statement: [Melfitani, hasGentilicForm, Melfitano]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGentilicForm Context triple: [Melfitani, hasGentilicForm, Melfitano]
-
A.
usesGentilicFor
Indicates that one entity refers to another using a gentilic (a demonym or term denoting origin, nationality, or regional affiliation).
-
B.
gentilicium
Indicates that an entity’s family or clan affiliation is expressed through a gentilic (family) name.
-
C.
hasGrammaticalGender
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
-
D.
gentilicLanguage
Indicates that a language is associated with or derived from a particular gentilic (demonym) for a people or place.
-
E.
hasLatinizedName
Indicates that an entity is associated with a version of its name that has been converted into Latin form or spelling.
- F. None of above. chosen
Provenance (4 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_69f05b0a5cc0819094828367ae204b70 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
| PDg | Predicate description generation | batch_69f74061c440819080434155c2d60341 |
completed | May 3, 2026, 12:32 p.m. |
Created at: April 28, 2026, 8:17 a.m.