Triple
T33990082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow airports |
E871517
|
entity |
| Predicate | numberOfMajorAirports |
P205273
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Moscow airports, numberOfMajorAirports, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMajorAirports Context triple: [Moscow airports, numberOfMajorAirports, 4]
-
A.
hasMajorAirport
Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
-
B.
isMajorCargoAirport
Indicates that an airport primarily handles large volumes of cargo traffic and serves as a significant freight hub.
-
C.
isMajorRegionalAirportFor
Indicates that an airport serves as a primary or significant air travel hub for a particular region.
-
D.
hasMinorAirport
Indicates that a location or region is served by at least one smaller, secondary, or non-major airport.
-
E.
largestAirport
Indicates that one airport is the largest (typically by area, traffic, or capacity) among a specified set or within a given region.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:50 a.m.