Triple
T37892874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surveyor 6 |
E945195
|
entity |
| Predicate | hopDistance |
P189585
|
FINISHED |
| Object | about 2.5 meters |
—
|
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: about 2.5 meters | Statement: [Surveyor 6, hopDistance, about 2.5 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hopDistance Context triple: [Surveyor 6, hopDistance, about 2.5 meters]
-
A.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
B.
wireDistance
Indicates the physical separation or length of wire between two connected points or components.
-
C.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
D.
distanceToTerminal
Indicates the measured or calculated distance from a given entity or location to a specified terminal point or facility.
-
E.
distanceToHeilbronn
Indicates the spatial distance between a given entity or location and the city of Heilbronn.
- 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_69f76ef0e8708190987c7254ed8c7abe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc36bcac48190a726b40442c094d1 |
completed | May 6, 2026, 10:40 p.m. |
Created at: May 3, 2026, 4:19 p.m.