Triple
T421773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iceland |
E8117
|
entity |
| Predicate | literacyRate |
P10080
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Iceland, literacyRate, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literacyRate Context triple: [Iceland, literacyRate, high]
-
A.
literacyStatus
chosen
Indicates whether an entity possesses the ability to read and write, or its level of literacy.
-
B.
historicallyDominantLanguageOfHigherEducationIn
Indicates that a language has historically been the primary or prevailing medium of instruction and scholarly communication in institutions of higher education within a given place or region.
-
C.
educatedIn
Indicates that an entity received education or formal training at a specified institution or place.
-
D.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
E.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec0e9dc81908c08b209ce5278ef |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.