Triple
T7371644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Louis Downtown Airport |
E170017
|
entity |
| Predicate | distanceFromDowntownStLouisMiles |
P1299
|
FINISHED |
| Object | approximately 3 |
—
|
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 | Statement: [St. Louis Downtown Airport, distanceFromDowntownStLouisMiles, approximately 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDowntownStLouisMiles Context triple: [St. Louis Downtown Airport, distanceFromDowntownStLouisMiles, approximately 3]
-
A.
distanceToStLouis
Indicates the measured distance between a given entity’s location and the city of St. Louis.
-
B.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
-
D.
distanceFromDesMoines
Indicates the physical distance between a given location and the city of Des Moines.
-
E.
distanceToLittleRock
Indicates the spatial distance between a given entity and the location of Little Rock.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f18451d88190ad4a2674279bb703 |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.