Triple
T7778030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Dauphine |
E221442
|
entity |
| Predicate | currentBuildings |
P78939
|
FINISHED |
| Object | many façades altered or rebuilt over centuries |
—
|
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: many façades altered or rebuilt over centuries | Statement: [Place Dauphine, currentBuildings, many façades altered or rebuilt over centuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentBuildings Context triple: [Place Dauphine, currentBuildings, many façades altered or rebuilt over centuries]
-
A.
currentBuilding
Indicates that an entity is located in, associated with, or belongs to the building that is relevant in the current context.
-
B.
publicBuilding
Indicates that a building is designated for public use or access, typically serving communal, governmental, or civic functions.
-
C.
buildingCurrentName
Indicates the name currently used to refer to a given building.
-
D.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
E.
buildingStructure
Indicates that one entity is a structural component or physical part that forms, supports, or constitutes the construction of another entity.
- F. None of above. chosen
Provenance (4 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
| PDg | Predicate description generation | batch_69cae7e47c5c8190bca90d45b3cdc25e |
completed | March 30, 2026, 9:15 p.m. |
Created at: March 30, 2026, 4:16 p.m.