Triple
T2180804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place de la Bastille |
E49036
|
entity |
| Predicate | citySquareType |
P16688
|
FINISHED |
| Object | traffic roundabout |
—
|
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: traffic roundabout | Statement: [Place de la Bastille, citySquareType, traffic roundabout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citySquareType Context triple: [Place de la Bastille, citySquareType, traffic roundabout]
-
A.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
-
B.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
C.
mainSquare
Indicates that a location serves as the primary or central public square of a town or city.
-
D.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
E.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.