Triple
T989135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Chief |
E21346
|
entity |
| Predicate | approximateDistanceMiles |
P7750
|
FINISHED |
| Object | 2250 |
—
|
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: 2250 | Statement: [Southwest Chief, approximateDistanceMiles, 2250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceMiles Context triple: [Southwest Chief, approximateDistanceMiles, 2250]
-
A.
approximateMileMarker
Indicates an estimated or not precisely measured position along a route expressed in miles.
-
B.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
C.
distance
chosen
Indicates the spatial separation or length between two points, objects, or locations.
-
D.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
E.
distanceCharacteristic
Indicates a relationship where an entity is described or constrained by some property or measure of distance (e.g., range, spacing, or separation).
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4aa16f081909dcc7a7ce3fb1b64 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.