Triple
T29296278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dingboche |
E742839
|
entity |
| Predicate | typicalStopoverDuration |
P203534
|
FINISHED |
| Object | 1–2 days for acclimatization |
—
|
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: 1–2 days for acclimatization | Statement: [Dingboche, typicalStopoverDuration, 1–2 days for acclimatization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStopoverDuration Context triple: [Dingboche, typicalStopoverDuration, 1–2 days for acclimatization]
-
A.
typicalStopoverCity
Indicates that a city commonly serves as an intermediate stop or layover point in a journey between other locations.
-
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.
aircraftStopover
Indicates that an aircraft makes an intermediate stop at a specific location during its journey between origin and final destination.
-
D.
typicalOvernightStop
Indicates that a location is commonly used as an overnight stopping point along a route or journey.
-
E.
stopoverLocation
Indicates that an entity makes an intermediate stop or layover at a specified location during a journey or route.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_6a019dfc69fc8190b0d80279a6216ba7 |
completed | May 11, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_6a019d54586c81908292d4880db9fad2 |
completed | May 11, 2026, 9:11 a.m. |
| PDg | Predicate description generation | batch_6a019dfba430819089f5609d89fbb7d9 |
completed | May 11, 2026, 9:14 a.m. |
Created at: April 28, 2026, 1:06 p.m.