Triple
T1419273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Eastern Airlines |
E31985
|
entity |
| Predicate | numberOfDestinations |
P13065
|
FINISHED |
| Object | over 200 |
—
|
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: over 200 | Statement: [China Eastern Airlines, numberOfDestinations, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDestinations Context triple: [China Eastern Airlines, numberOfDestinations, over 200]
-
A.
servesDestinationCount
chosen
Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
-
B.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
C.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
-
D.
numberOfHostCities
Indicates the count of distinct cities that have hosted or will host a particular event or activity.
-
E.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c40631e881909ddf81a2eb84af1c |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.