Triple
T11448146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibiasky comet |
E271316
|
entity |
| Predicate | hasFictionalOrbitType |
P7214
|
FINISHED |
| Object | near-Earth trajectory |
—
|
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: near-Earth trajectory | Statement: [Dibiasky comet, hasFictionalOrbitType, near-Earth trajectory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalOrbitType Context triple: [Dibiasky comet, hasFictionalOrbitType, near-Earth trajectory]
-
A.
isOrbital
Indicates that one entity moves in a curved, repeating path around another entity due to gravitational or similar central forces.
-
B.
hasOrbitalCharacteristic
Indicates that an entity possesses a specific property or feature related to its orbit, such as shape, period, inclination, or other orbital parameters.
-
C.
orbitType
chosen
Indicates the specific kind or classification of an object's orbit in relation to the body it revolves around.
-
D.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
E.
hasOrbitalRegion
Indicates that one entity occupies, lies within, or is associated with a specific orbital zone or region around another body.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c6d4890819082fb4a670feb2629 |
completed | April 9, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d7e7162b288190a0bfb89f7eb747c7 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.