Triple
T30023954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGC 5189 |
E762827
|
entity |
| Predicate | hasKinematicComplexity |
P168378
|
FINISHED |
| Object | multiple outflows |
—
|
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: multiple outflows | Statement: [NGC 5189, hasKinematicComplexity, multiple outflows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKinematicComplexity Context triple: [NGC 5189, hasKinematicComplexity, multiple outflows]
-
A.
hasKinematicUse
Indicates that one entity is used in a kinematic context or role within the motion or movement behavior of another entity.
-
B.
hasKinematicProperty
Indicates that an entity possesses a specific motion-related characteristic, such as velocity, acceleration, or trajectory.
-
C.
hasKinematicRole
Indicates that an entity participates in a motion or physical interaction with a specific kinematic function or role (e.g., mover, pivot, link) within a dynamic system.
-
D.
hasKinematicRegime
Indicates that an entity is associated with, or operates within, a particular kinematic regime or motion behavior.
-
E.
hasKinetics
Indicates that one entity is associated with the kinetic properties or rate-related behavior of another entity in a process or reaction.
- 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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f679a9e95081908aecded7962e0c87 |
completed | May 2, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 6:48 p.m.