Triple
T37905260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Ice Empire |
E945527
|
entity |
| Predicate | hasPopulationCondition |
P9067
|
FINISHED |
| Object | sparsely populated |
—
|
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: sparsely populated | Statement: [Spanish Ice Empire, hasPopulationCondition, sparsely populated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationCondition Context triple: [Spanish Ice Empire, hasPopulationCondition, sparsely populated]
-
A.
hasPopulationStatus
chosen
Indicates the current demographic condition or classification of a population associated with an entity.
-
B.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
C.
hasIndicationPopulation
Indicates that a medical indication is specifically applicable to, or defined for, a particular population group.
-
D.
hasCampPopulation
Indicates that a particular camp has a specified number or composition of people residing in it.
-
E.
typicalPopulationThreshold
Indicates the population level above which a place is typically considered to meet a particular classification or status.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fff09dae088190bd8460060d778feb |
completed | May 10, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69fff0027c5c8190baa5c7a15852cbe0 |
completed | May 10, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:20 p.m.