Triple
T427832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemnitz Hauptbahnhof |
E9646
|
entity |
| Predicate | hasRebuiltDate |
P13795
|
FINISHED |
| Object | late 19th century |
—
|
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: late 19th century | Statement: [Chemnitz Hauptbahnhof, hasRebuiltDate, late 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRebuiltDate Context triple: [Chemnitz Hauptbahnhof, hasRebuiltDate, late 19th century]
-
A.
rebuiltFor
Indicates that one entity has been reconstructed, renovated, or modified specifically to serve the needs, purposes, or use of another entity.
-
B.
reconstructedAfter
Indicates that one entity has been rebuilt, restored, or reassembled following the occurrence or existence of another entity or event.
-
C.
rebuiltUnder
Indicates that an entity was reconstructed or restored while being subject to the authority, control, or governance of another entity.
-
D.
reconstructionBuilt
Indicates that one entity carried out or was responsible for constructing a rebuilt or restored version of another entity.
-
E.
reassessedAfter
Indicates that one entity is evaluated or reviewed again at a time point that occurs after another specified event or assessment.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eed7f3508190995dcd39586ed614 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd7a3608190b8785c7b7205f6c1 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.