Triple
T404041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How Will I Know |
E9345
|
entity |
| Predicate | chartPositionCanada |
P11138
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [How Will I Know, chartPositionCanada, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chartPositionCanada Context triple: [How Will I Know, chartPositionCanada, 1]
-
A.
hasPopulationRankInCanada
Indicates the relative position of an entity’s population size compared to other entities within Canada.
-
B.
countryScope
Indicates that something is limited to, applicable within, or defined at the level of a specific country.
-
C.
countryLed
Indicates that one country serves as the leader, head, or primary directing authority over another country in a given context.
-
D.
countryTargeted
Indicates that a particular country is the intended object or focus of an action, operation, or influence.
-
E.
cantonPosition
Indicates the relative placement or arrangement of a canton within a larger geographic or administrative context.
- F. None of above. chosen
Provenance (4 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eca226fc81909d6ccc38a637daa6 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e97066e8819083cc1b3a421b9650 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea60e590819081779a6510918d9b |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.