Triple
T647017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US Airways |
E11262
|
entity |
| Predicate | servedDestinationsAtPeak |
P4936
|
FINISHED |
| Object | over 190 destinations |
—
|
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 190 destinations | Statement: [US Airways, servedDestinationsAtPeak, over 190 destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedDestinationsAtPeak Context triple: [US Airways, servedDestinationsAtPeak, over 190 destinations]
-
A.
servesDestinationCount
Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
-
B.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
-
C.
historicalPeak
chosen
Indicates that the related value or state represents the highest level ever reached by something within a historical or recorded time frame.
-
D.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
E.
dailyRidershipPeak
Indicates that the relationship specifies the highest number of riders or users recorded for a service or system within a single day.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1cb24481909d3b41a56b29dee9 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.