Triple
T13346868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Schaumburg-Lippe |
E317974
|
entity |
| Predicate | populationAround1900 |
P5555
|
FINISHED |
| Object | about 45,000 inhabitants |
—
|
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: about 45,000 inhabitants | Statement: [Prince of Schaumburg-Lippe, populationAround1900, about 45,000 inhabitants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationAround1900 Context triple: [Prince of Schaumburg-Lippe, populationAround1900, about 45,000 inhabitants]
-
A.
populationStatus19thCentury
Indicates the population condition or demographic status of an entity during the 19th century.
-
B.
hasPopulationAsOf
chosen
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
C.
hostsPopulation
Indicates that an entity serves as the living environment or container in which a particular population exists or resides.
-
D.
populationScale
Indicates the relative size or magnitude of a population, typically categorizing it into broad scale levels (e.g., small, medium, large).
-
E.
religiousCompositionHistorical
Indicates the historical distribution or makeup of religious affiliations within a population or group over time.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e89c65c819093f3bea11d6073c5 |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.