Triple
T16305720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qinghai–Tibet Railway |
E395904
|
entity |
| Predicate | totalLength_km |
P69216
|
FINISHED |
| Object | about 1956 |
—
|
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 1956 | Statement: [Qinghai–Tibet Railway, totalLength_km, about 1956]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalLength_km Context triple: [Qinghai–Tibet Railway, totalLength_km, about 1956]
-
A.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
B.
trackLengthApproxKm
chosen
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
C.
totalRouteLength
Indicates the overall distance or length of an entire route when all its segments are combined.
-
D.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
E.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d5619081909d0f8157cc487877 |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.