Triple
T3824395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YUL |
E88650
|
entity |
| Predicate | associatedWithWMOCode |
P9474
|
FINISHED |
| Object | 71627 |
—
|
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: 71627 | Statement: [YUL, associatedWithWMOCode, 71627]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithWMOCode Context triple: [YUL, associatedWithWMOCode, 71627]
-
A.
WMO code
chosen
Indicates that an entity is associated with a specific identifier defined by the World Meteorological Organization (WMO) coding system.
-
B.
associatedWithWeather
Indicates a relationship where something is connected or related to weather conditions or phenomena.
-
C.
associatedWithPrecipitationType
Indicates that there is a relationship between an entity and a specific type or category of precipitation (such as rain, snow, or hail).
-
D.
associatedWithICAOcode
Indicates a relationship where an entity is linked to, or identified by, a specific ICAO (International Civil Aviation Organization) code.
-
E.
associatedWithFlag
Indicates a relationship where an entity is linked or connected to a particular flag, such as a national, organizational, or symbolic banner.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.