Triple
T187967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Shore Limited |
E4023
|
entity |
| Predicate | journeyTime |
P1526
|
FINISHED |
| Object | approximately 19–20 hours Chicago–New York |
—
|
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 19–20 hours Chicago–New York | Statement: [Lake Shore Limited, journeyTime, approximately 19–20 hours Chicago–New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: journeyTime Context triple: [Lake Shore Limited, journeyTime, approximately 19–20 hours Chicago–New York]
-
A.
flightDuration
chosen
Indicates the length of time that a specific flight takes from departure to arrival.
-
B.
time
Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
-
C.
peakRouteMileage
Indicates the maximum total distance covered by a particular route over a specified period or under peak operating conditions.
-
D.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
E.
timeDescribedAs
Indicates that a specific time or temporal interval is characterized, labeled, or expressed using a particular description or representation.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594940e48190a3d8efbce46241c3 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.