Triple
T197960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voyager 1 |
E4038
|
entity |
| Predicate | isMostDistantHumanMadeObject |
P8104
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Voyager 1, isMostDistantHumanMadeObject, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostDistantHumanMadeObject Context triple: [Voyager 1, isMostDistantHumanMadeObject, true]
-
A.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromEarth
Indicates the measured or calculated spatial separation between an entity and the planet Earth.
-
D.
countryClosestTo
Indicates the relationship where one country is geographically nearer to a given reference point or entity than any other country.
-
E.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25be47ea881909c296b30a0d47a65 |
completed | Feb. 28, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69a25b47481c8190add47c641c977bb9 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25be349588190aedde33d80682344 |
completed | Feb. 28, 2026, 3:07 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.