Triple
T1336203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri–Kansas–Texas Railroad |
E28754
|
entity |
| Predicate | completedLineToSanAntonio |
P27885
|
FINISHED |
| Object | 1887 |
—
|
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: 1887 | Statement: [Missouri–Kansas–Texas Railroad, completedLineToSanAntonio, 1887]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: completedLineToSanAntonio Context triple: [Missouri–Kansas–Texas Railroad, completedLineToSanAntonio, 1887]
-
A.
wentTo
Indicates that one entity traveled or moved from its original location to another specified place.
-
B.
distanceFromDallas
Indicates the measured distance between a given place or entity and the city of Dallas.
-
C.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
-
D.
relocationToHouston
Indicates a change of location in which an entity moves or is transferred to Houston as its new place of residence or operation.
-
E.
finalCity
Indicates that a given city is the last or ultimate city associated with an entity within a sequence, process, or journey.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c1bf31988190a659f48fe018f4bc |
completed | March 1, 2026, 10:46 p.m. |
Created at: March 1, 2026, 7:55 p.m.