Triple
T5483297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asinelli Tower |
E123516
|
entity |
| Predicate | hasCityCenterLocation |
P25976
|
FINISHED |
| Object | historic center of Bologna |
—
|
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: historic center of Bologna | Statement: [Asinelli Tower, hasCityCenterLocation, historic center of Bologna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityCenterLocation Context triple: [Asinelli Tower, hasCityCenterLocation, historic center of Bologna]
-
A.
hasCityCentreLocation
chosen
Indicates that something is located in, or directly associated with, the central area of a city.
-
B.
notableCityCenter
Indicates that a location serves as a prominent or significant central area within a city.
-
C.
centralLocation
Indicates that one entity serves as the primary or central place associated with another entity.
-
D.
hasPopulationCenter
Indicates that an area, region, or administrative unit contains or is served by a primary settlement or population hub.
-
E.
isDowntownCoreOf
Indicates that a location constitutes the central, most urbanized and commercially dense area of a larger city or metropolitan region.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.