Triple
T25127306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strada Smârdan |
E629428
|
entity |
| Predicate | hasRenovatedBuildings |
P93641
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Strada Smârdan, hasRenovatedBuildings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRenovatedBuildings Context triple: [Strada Smârdan, hasRenovatedBuildings, yes]
-
A.
hasRenovation
Indicates that an entity has undergone, is undergoing, or is associated with a renovation process or renovation event.
-
B.
wasRenovatedFor
Indicates that an existing entity underwent renovation specifically to serve the needs, purposes, or use of another entity.
-
C.
hasRenovatedFacade
chosen
Indicates that an entity has a building whose exterior facade has been renovated or updated.
-
D.
mayBeRenovatedFor
Indicates that something has the potential to be renovated or modified for use by or in connection with another entity or purpose.
-
E.
renovatedAfter
Indicates that one entity was renovated at a later time than another entity.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 18, 2026, 6:28 a.m.