Triple
T5040731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Market (Riga) |
E113537
|
entity |
| Predicate | pavilionType |
P55703
|
FINISHED |
| Object | meat pavilion |
—
|
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: meat pavilion | Statement: [Central Market (Riga), pavilionType, meat pavilion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pavilionType Context triple: [Central Market (Riga), pavilionType, meat pavilion]
-
A.
hasPavilionFunction
chosen
Indicates that something serves the role or function of a pavilion, such as providing a designated space or facility for specific activities or purposes.
-
B.
hasPavilion
Indicates that one entity possesses, includes, or is associated with a pavilion as part of its structure, property, or facilities.
-
C.
furnishingType
Indicates the type or category of furnishings associated with an entity, such as a property or room.
-
D.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
E.
chairType
Indicates the specific kind or category of chair that an entity is classified as.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73dd27fc8190817e53311ea3f706 |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71529d608190a53470ba6c14bb1d |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.