Triple
T5588605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alsike |
E146818
|
entity |
| Predicate | urbanAreaStatus |
P749
|
FINISHED |
| Object | tätort |
—
|
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: tätort | Statement: [Alsike, urbanAreaStatus, tätort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanAreaStatus Context triple: [Alsike, urbanAreaStatus, tätort]
-
A.
cityStatusContext
Indicates the contextual status or role that a city holds within a broader administrative, political, or situational framework.
-
B.
cityStatusUntil
Indicates the period up to a specified time during which a place holds or held a particular city status.
-
C.
urbanAreaType
chosen
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
D.
urbanRegenerationStatus
Indicates the current stage or condition of efforts to renew, redevelop, or revitalize an urban area.
-
E.
statusInUrbanAreas
Indicates the condition, prevalence, or situation of something specifically within urban areas.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209e892c8190b936a05ef2a14d36 |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.