Triple
T25669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Lindbergh |
E512
|
entity |
| Predicate | flightDistance |
P1525
|
FINISHED |
| Object | approximately 3,600 miles |
—
|
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 3,600 miles | Statement: [Charles Lindbergh, flightDistance, approximately 3,600 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightDistance Context triple: [Charles Lindbergh, flightDistance, approximately 3,600 miles]
-
A.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
B.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
C.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
D.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
-
E.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246d6aca88190a86b7c41d497bacd |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.