Triple
T13760576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susaninskaya Square |
E330594
|
entity |
| Predicate | hasMapFeatureType |
P39038
|
FINISHED |
| Object | square |
—
|
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: square | Statement: [Susaninskaya Square, hasMapFeatureType, square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMapFeatureType Context triple: [Susaninskaya Square, hasMapFeatureType, square]
-
A.
hasMapType
Indicates that one entity is associated with a specific type or category of map.
-
B.
hasMapRegion
Indicates that an entity is associated with, or belongs to, a specific geographic or logical map region.
-
C.
hasFeatureClass
chosen
Indicates that an entity is associated with, or categorized under, a particular feature class that characterizes its type or nature.
-
D.
hasMapframe
Indicates that an entity is associated with an embedded, interactive map frame representation of its geographic location or area.
-
E.
hasImageryType
Indicates that one entity is associated with a specific kind or category of imagery (such as visual style, medium, or representation type) used to depict or describe it.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0223ab9081909db05334860405e0 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:09 p.m.