Triple
T1088655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Kilda |
E24109
|
entity |
| Predicate | depopulationYear |
P18224
|
FINISHED |
| Object | 1930 |
—
|
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: 1930 | Statement: [St Kilda, depopulationYear, 1930]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depopulationYear Context triple: [St Kilda, depopulationYear, 1930]
-
A.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
B.
reducedPopulationOf
Indicates a relationship where one entity has caused a decrease in the size or number of individuals in a population of another entity.
-
C.
yearOfDisappearance
chosen
Indicates the specific year in which an entity disappeared or ceased to be present.
-
D.
declineBeganInDecade
Indicates that the period of decline for an entity or phenomenon started during the specified decade.
-
E.
demographicScope
Indicates the specific population group or demographic segment to which something (e.g., a policy, study, product, or service) is targeted or applicable.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97d85708190a1630256648aa4a2 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.