Triple
T5223642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rialto Bridge |
E117930
|
entity |
| Predicate | hasNumberOfArchwaysForShops |
P9131
|
FINISHED |
| Object | two rows |
—
|
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: two rows | Statement: [Rialto Bridge, hasNumberOfArchwaysForShops, two rows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfArchwaysForShops Context triple: [Rialto Bridge, hasNumberOfArchwaysForShops, two rows]
-
A.
hasAisles
Indicates that a location or structure contains one or more aisles as part of its internal layout or organization.
-
B.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
-
C.
numberOfAisles
Indicates the total count of aisles associated with or contained within a given entity.
-
D.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
E.
hasNumberOfArches
chosen
Indicates the relationship specifying how many arches are present in or associated with 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7abd3ed48190bfd8d2f2ca399741 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.