Triple
T20446871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucana IV |
E501538
|
entity |
| Predicate | hasKinematicUse |
P140145
|
FINISHED |
| Object | measures mass-to-light ratios in faint systems |
—
|
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: measures mass-to-light ratios in faint systems | Statement: [Tucana IV, hasKinematicUse, measures mass-to-light ratios in faint systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKinematicUse Context triple: [Tucana IV, hasKinematicUse, measures mass-to-light ratios in faint systems]
-
A.
hasKinematicProperty
Indicates that an entity possesses a specific motion-related characteristic, such as velocity, acceleration, or trajectory.
-
B.
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.
-
C.
hasKinematicRegime
Indicates that an entity is associated with, or operates within, a particular kinematic regime or motion behavior.
-
D.
hasKinetics
Indicates that one entity is associated with the kinetic properties or rate-related behavior of another entity in a process or reaction.
-
E.
hasKinematicCenterApprox
Indicates that an entity has an approximate kinematic center location or value associated with it.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfe57a8819094bd3d324bd567f5 |
completed | April 20, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:32 a.m.