Triple
T32167331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teatr Wielki Square |
E821614
|
entity |
| Predicate | nearRoute |
P61270
|
FINISHED |
| Object | historic processional routes in Warsaw |
—
|
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: historic processional routes in Warsaw | Statement: [Teatr Wielki Square, nearRoute, historic processional routes in Warsaw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearRoute Context triple: [Teatr Wielki Square, nearRoute, historic processional routes in Warsaw]
-
A.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
B.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
C.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
D.
namedAfterNearbyPlace
Indicates that an entity’s name is derived from or inspired by a geographically nearby place.
-
E.
nearDowntown
Indicates that one location is situated close to or within a short distance of a city’s downtown area.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6ba2089588190808706cc40fea7d6 |
completed | May 3, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:33 a.m.