Triple
T33543232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piazza della Cancelleria |
E859130
|
entity |
| Predicate | hasNearbyBusCorridor |
P96747
|
FINISHED |
| Object | Corso Vittorio Emanuele II |
—
|
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: Corso Vittorio Emanuele II | Statement: [Piazza della Cancelleria, hasNearbyBusCorridor, Corso Vittorio Emanuele II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyBusCorridor Context triple: [Piazza della Cancelleria, hasNearbyBusCorridor, Corso Vittorio Emanuele II]
-
A.
hasNearbyTransportationCorridor
chosen
Indicates that an entity is located close to a significant transportation route or corridor, such as a road, railway, or transit line.
-
B.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
C.
nearbyBusStation
Indicates that a bus station is located close to a given reference point or entity.
-
D.
hasNearbyLine
Indicates that one entity is located close to, or in the vicinity of, a particular line or linear feature.
-
E.
hasAdjacentBusStation
Indicates that one location has a bus station situated directly next to or very near it.
- 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_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 1, 2026, 1:39 a.m.