Triple
T19972393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican railroads |
E480110
|
entity |
| Predicate | primaryFocusSinceLate20thCentury |
P138094
|
FINISHED |
| Object | cargo services |
—
|
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: cargo services | Statement: [Mexican railroads, primaryFocusSinceLate20thCentury, cargo services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFocusSinceLate20thCentury Context triple: [Mexican railroads, primaryFocusSinceLate20thCentury, cargo services]
-
A.
functionDuring20thCentury
Indicates that the function, role, or operation of one entity with respect to another occurred at some time during the 20th century.
-
B.
statusIn20thCentury
Indicates that an entity held a particular status, condition, or classification specifically during the 20th century.
-
C.
lostCentury
Indicates that a particular century or era has been forgotten, obscured, or is missing from records or collective knowledge.
-
D.
popularInCentury
Indicates that something was widely liked, influential, or commonly recognized during a specified century.
-
E.
century
Indicates that an entity is associated with, occurs in, or belongs to a particular 100-year time period.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bca94c0819095c902a411c4c4b8 |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:54 p.m.