Triple
T33543238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piazza della Cancelleria |
E859130
|
entity |
| Predicate | hasNearbyMarketArea |
P141258
|
FINISHED |
| Object | Campo de' Fiori |
—
|
NE NERFINISHED |
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: Campo de' Fiori | Statement: [Piazza della Cancelleria, hasNearbyMarketArea, Campo de' Fiori]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMarketArea Context triple: [Piazza della Cancelleria, hasNearbyMarketArea, Campo de' Fiori]
-
A.
hasNearbyCommercialFacilities
Indicates that a place is located close to one or more commercial facilities, such as shops, restaurants, or other businesses.
-
B.
nearbyCountryMarket
Indicates that a market is located in a country that is geographically close to another specified country.
-
C.
nearbyStateMarket
Indicates that a market is located in a state that is geographically close to the reference state.
-
D.
hasNearbyGeographicalArea
chosen
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
Created at: May 1, 2026, 1:39 a.m.