Triple
T2114719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guglielmo |
E42580
|
entity |
| Predicate | typicalNameUsageRegion |
P15483
|
FINISHED |
| Object | 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: Southern Europe | Statement: [Guglielmo, typicalNameUsageRegion, Southern Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNameUsageRegion Context triple: [Guglielmo, typicalNameUsageRegion, Southern Europe]
-
A.
hasTypicalUsageRegion
chosen
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
B.
regionNamedAfter
Indicates that a geographic region derives its name from a specific person, place, event, or other entity.
-
C.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
D.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
E.
regionallyRecognizedAs
Indicates that an entity is acknowledged or designated under a specific name, status, or classification within a particular geographic region or locality.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0724e08190a0a4210d86261d6d |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.