Triple
T35125092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlas V 500 series |
E1014279
|
entity |
| Predicate | configurationRange |
P182575
|
FINISHED |
| Object | Atlas V 501 |
—
|
NE NERFINISHED |
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: Atlas V 501 | Statement: [Atlas V 500 series, configurationRange, Atlas V 501]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: configurationRange Context triple: [Atlas V 500 series, configurationRange, Atlas V 501]
-
A.
coreRange
Indicates the primary spatial or temporal extent within which an entity, phenomenon, or relationship is predominantly present or valid.
-
B.
controlRange
Indicates the spatial or contextual extent within which an entity can exert control or influence over another entity or process.
-
C.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
D.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
E.
designedRange
Indicates the intended or specified range within which something is designed to operate or be effective.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7904a770481908ef3f788e51e8dba |
completed | May 3, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:01 p.m.