Triple
T801220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Peninsula |
E17130
|
entity |
| Predicate | UNM49Region |
P18845
|
FINISHED |
| Object | 039-Southern Europe |
—
|
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: 039-Southern Europe | Statement: [Italian Peninsula, UNM49Region, 039-Southern Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UNM49Region Context triple: [Italian Peninsula, UNM49Region, 039-Southern Europe]
-
A.
censusRegion
Indicates the broader census-defined geographic region in which an entity (such as a place or population unit) is located or classified.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
metropolitanStatisticalArea
Indicates that one place is part of, or classified within, a specific metropolitan statistical area as defined for demographic or economic analysis.
-
D.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
E.
isEasternmostCountyOf
Indicates that a county is the geographically farthest east within the boundaries of a specified larger region or jurisdiction.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cc75e88190bd35aabe51051b51 |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5133bf88190a613e96d1f7cffa7 |
completed | March 1, 2026, 8:44 p.m. |
| PDg | Predicate description generation | batch_69a4a58c0a84819094f07658dc651b36 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:38 p.m.