Triple
T3409303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italica |
E71850
|
entity |
| Predicate | urbanLayoutType |
P22625
|
FINISHED |
| Object | orthogonal street plan |
—
|
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: orthogonal street plan | Statement: [Italica, urbanLayoutType, orthogonal street plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanLayoutType Context triple: [Italica, urbanLayoutType, orthogonal street plan]
-
A.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
B.
urbanDevelopmentType
Indicates the specific category or nature of urban development associated with or applied to an entity (e.g., residential, commercial, mixed-use).
-
C.
urbanPlanningStyle
chosen
Indicates the characteristic approach or methodology used in planning and organizing urban spaces and development.
-
D.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
E.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb90754788190ab85e2bec020f99e |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.