Triple
T19972424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican railroads |
E480110
|
entity |
| Predicate | historicalPassengerRole |
P87595
|
FINISHED |
| Object | long-distance intercity travel |
—
|
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: long-distance intercity travel | Statement: [Mexican railroads, historicalPassengerRole, long-distance intercity travel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalPassengerRole Context triple: [Mexican railroads, historicalPassengerRole, long-distance intercity travel]
-
A.
hasHistoricalRoleAs
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
B.
roleHistoricallyAssociatedWith
chosen
Indicates that one role, position, or function has been historically linked or commonly associated with another entity, role, or context over time.
-
C.
shipHistoricalRole
Indicates the historical function or significance a ship had, such as its role in events, conflicts, or periods of service.
-
D.
hasNamesakeRoleInHistory
Indicates that an entity has a historical role or position that is the same as, or named after, another entity’s role in history.
-
E.
historicalPass
Indicates that an entity has successfully completed or passed a historical event, period, or examination related to history.
- 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_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. |
Created at: April 10, 2026, 1:54 p.m.