Triple
T9053302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaddafi era |
E216936
|
entity |
| Predicate | demographyImpact |
P3838
|
FINISHED |
| Object | rapid urbanization in Libya |
—
|
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: rapid urbanization in Libya | Statement: [Gaddafi era, demographyImpact, rapid urbanization in Libya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographyImpact Context triple: [Gaddafi era, demographyImpact, rapid urbanization in Libya]
-
A.
demographicImpact
chosen
Indicates how an action, event, or condition affects the size, structure, or composition of a population.
-
B.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
-
C.
demographicChallenge
Indicates a situation where population trends (such as aging, low birth rates, or migration patterns) create significant social, economic, or policy pressures that must be addressed.
-
D.
population
Indicates the total number of individuals living in or present within a specified area or group.
-
E.
demographicBasis
Indicates that something is determined, classified, or justified based on demographic characteristics such as age, gender, ethnicity, or similar population attributes.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a71a9d88190949ef9dc6816d6ab |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.