Triple
T8715127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viktualienmarkt |
E206873
|
entity |
| Predicate | hasNumberOfStalls |
P43082
|
FINISHED |
| Object | over 100 |
—
|
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: over 100 | Statement: [Viktualienmarkt, hasNumberOfStalls, over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStalls Context triple: [Viktualienmarkt, hasNumberOfStalls, over 100]
-
A.
hasTypeOfStalls
Indicates that an entity features or includes stalls of a particular type or category.
-
B.
numberOfStalls
chosen
Indicates the quantity of stalls associated with or contained within a given entity or location.
-
C.
hasStalls
Indicates that an entity contains, provides, or is equipped with stalls (e.g., booths, compartments, or vendor stands).
-
D.
hasStabling
Indicates that one entity provides or contains stabling facilities (such as stalls or accommodation) for another, typically for animals like horses.
-
E.
numberOfBays
Indicates the count of distinct bays associated with or contained within a given 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.