Triple
T7803519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hackescher Markt |
E180488
|
entity |
| Predicate | timePeriodOfMajorRenovation |
P54016
|
FINISHED |
| Object | 1990s |
—
|
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: 1990s | Statement: [Hackescher Markt, timePeriodOfMajorRenovation, 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfMajorRenovation Context triple: [Hackescher Markt, timePeriodOfMajorRenovation, 1990s]
-
A.
renovationPeriod
Indicates the time span during which an object, structure, or entity undergoes renovation or refurbishment.
-
B.
renovatedAfter
Indicates that one entity was renovated at a later time than another entity.
-
C.
renovationYear
Indicates the year in which an entity underwent renovation or significant refurbishment.
-
D.
majorRedevelopmentPeriod
chosen
Indicates a time span during which a place or structure underwent significant redevelopment or large-scale renovation.
-
E.
hasMajorReconstruction
Indicates that an entity has undergone a significant or extensive reconstruction or renovation.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:34 p.m.