Triple
T724158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grüner Markt |
E14685
|
entity |
| Predicate | typicalVendors |
P17473
|
FINISHED |
| Object | local food vendors |
—
|
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: local food vendors | Statement: [Grüner Markt, typicalVendors, local food vendors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVendors Context triple: [Grüner Markt, typicalVendors, local food vendors]
-
A.
dataVendor
Indicates a relationship where one entity serves as a provider or supplier of data to another entity.
-
B.
typicalProvider
chosen
Indicates that one entity commonly or characteristically serves as a provider of goods, services, or resources to another entity.
-
C.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
-
D.
associatedRetailer
Indicates that one entity has a business or operational connection with a particular retailer, such as partnership, distribution, or sales affiliation.
-
E.
typicalEmployerUnit
Indicates that one entity is the standard or characteristic organizational unit that employs or is expected to employ another entity.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a6ab508190b70a05a9d77829a5 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.