Triple
T20252212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Most Grunwaldzki |
E498584
|
entity |
| Predicate | isUrbanStructure |
P67280
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Most Grunwaldzki, isUrbanStructure, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanStructure Context triple: [Most Grunwaldzki, isUrbanStructure, yes]
-
A.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
-
B.
isUrbanNode
Indicates that a location or entity functions as an urban center or node within a city or metropolitan network.
-
C.
isUrbanForm
chosen
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
D.
isUrbanStreet
Indicates that a given street is located within an urban area or city environment rather than a rural or suburban setting.
-
E.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a8b8488190b344df7a65f59684 |
completed | April 20, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.