Triple
T26692061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stoneley waves |
E672912
|
entity |
| Predicate | haveParticleMotion |
P45058
|
FINISHED |
| Object | concentrated near the boundary |
—
|
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: concentrated near the boundary | Statement: [Stoneley waves, haveParticleMotion, concentrated near the boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveParticleMotion Context triple: [Stoneley waves, haveParticleMotion, concentrated near the boundary]
-
A.
hasVerticalMotion
Indicates that an entity is undergoing or exhibiting motion in the vertical direction (upward or downward).
-
B.
hasParticleType
Indicates that an entity is associated with, composed of, or characterized by a specific type or category of particle.
-
C.
modelsMotionOf
Indicates that one entity provides a representation or simulation of the motion or movement behavior of another entity.
-
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.
hasMovementStructure
chosen
Indicates that one entity possesses or is characterized by a particular structure or pattern of movement.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6174310d48190b1ef1e515fed7990 |
completed | May 2, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:26 a.m.