Triple
T20023268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IR |
E494913
|
entity |
| Predicate | typicalStopsPattern |
P102636
|
FINISHED |
| Object | serves medium-size cities |
—
|
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: serves medium-size cities | Statement: [IR, typicalStopsPattern, serves medium-size cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStopsPattern Context triple: [IR, typicalStopsPattern, serves medium-size cities]
-
A.
typicalStopPattern
chosen
Indicates the usual or most common sequence or arrangement of stops associated with an entity’s operation or route.
-
B.
typicalStopoverRegion
Indicates the geographic region where an entity (such as a migrating animal or traveler) most commonly makes an intermediate stop during its journey.
-
C.
typicalStopoverCity
Indicates that a city commonly serves as an intermediate stop or layover point in a journey between other locations.
-
D.
typicalOvernightStop
Indicates that a location is commonly used as an overnight stopping point along a route or journey.
-
E.
stopsPattern
Indicates that one entity halts, interrupts, or prevents the continuation of a recurring or structured pattern involving another 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628a1ecc8190bf6ee0bedb61e0b8 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:35 p.m.