Triple
T6909576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian March |
E159895
|
entity |
| Predicate | ethnicallyMixedRegion |
P42257
|
FINISHED |
| Object | Italians |
—
|
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: Italians | Statement: [Julian March, ethnicallyMixedRegion, Italians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicallyMixedRegion Context triple: [Julian March, ethnicallyMixedRegion, Italians]
-
A.
hasEthnicallyMixedPopulation
chosen
Indicates that a population is composed of people from multiple distinct ethnic groups rather than being ethnically homogeneous.
-
B.
ethnoLinguisticRegionOf
Indicates that a region is defined or characterized by the shared ethnic and linguistic identity of the group associated with it.
-
C.
ethnogenesisRegion
Indicates the geographic region where the formation or emergence of an ethnic group took place.
-
D.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
E.
demographicRegion
Indicates that an entity is associated with, belongs to, or is characterized by a particular geographic or administrative region for demographic purposes.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9c00e948190b103a2b2a2738bb1 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.