Triple
T7554140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgrade–Bar railway |
E178613
|
entity |
| Predicate | MalaRijekaViaductLength |
P46595
|
FINISHED |
| Object | approximately 498 m |
—
|
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: approximately 498 m | Statement: [Belgrade–Bar railway, MalaRijekaViaductLength, approximately 498 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MalaRijekaViaductLength Context triple: [Belgrade–Bar railway, MalaRijekaViaductLength, approximately 498 m]
-
A.
hasSkyBridgeLength
Indicates the length measurement of a sky bridge connecting two structures or areas.
-
B.
bridgeLength
chosen
Indicates the physical length or span of a bridge structure.
-
C.
hasViaduct
Indicates that one entity possesses, includes, or is connected by a viaduct in relation to another entity.
-
D.
bridgeSpans
Indicates that a bridge extends across and connects two separate points or areas.
-
E.
wasWorldsLongestSuspensionBridgeSpan
Indicates that something held the record for having the longest main span of any suspension bridge in the world at a given time.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8b990148190b26a3a262cf538b3 |
completed | March 27, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:49 p.m.