Triple
T35206771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazon-Mostral |
E1016557
|
entity |
| Predicate | technologyLevelComparedToFederation |
P116408
|
FINISHED |
| Object | lower |
—
|
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: lower | Statement: [Kazon-Mostral, technologyLevelComparedToFederation, lower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologyLevelComparedToFederation Context triple: [Kazon-Mostral, technologyLevelComparedToFederation, lower]
-
A.
technologyLevelComparedTo
chosen
Indicates how the technological advancement of one entity compares relative to that of another entity.
-
B.
technologyLevel
Indicates the degree of technological advancement or sophistication associated with an entity relative to others or to a defined scale.
-
C.
featureLevelComparedTo
Indicates a comparative relationship between entities based on their feature level, specifying how one entity’s feature level ranks relative to another’s.
-
D.
technologyLevelComparedToPredecessor
Indicates how the technology level of an entity compares to that of its immediate predecessor.
-
E.
interoperabilityLevel
Indicates the degree to which different systems, components, or standards can effectively work together and exchange information.
- 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:02 p.m.