Triple
T14486631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing–Zhangjiakou intercity railway |
E359244
|
entity |
| Predicate | travelTimeBeijingToZhangjiakou |
P114416
|
FINISHED |
| Object | about 47 minutes at fastest |
—
|
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: about 47 minutes at fastest | Statement: [Beijing–Zhangjiakou intercity railway, travelTimeBeijingToZhangjiakou, about 47 minutes at fastest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeBeijingToZhangjiakou Context triple: [Beijing–Zhangjiakou intercity railway, travelTimeBeijingToZhangjiakou, about 47 minutes at fastest]
-
A.
distanceFromBeijing_km
Indicates the physical distance, measured in kilometers, between a given place or object and Beijing.
-
B.
approximateTravelTimeToDomodedovo
Indicates the estimated amount of time it typically takes to travel from a given location to Domodedovo.
-
C.
distanceFromBeijingCityCenter
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
D.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
-
E.
travelTimeToKrakówGłówny
Indicates the amount of time required to travel from a given location to Kraków Główny.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:20 a.m.