Triple
T9128821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyclomedusa |
E219030
|
entity |
| Predicate | hasUncertainAffinityWith |
P87259
|
FINISHED |
| Object | Cnidaria |
—
|
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: Cnidaria | Statement: [Cyclomedusa, hasUncertainAffinityWith, Cnidaria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUncertainAffinityWith Context triple: [Cyclomedusa, hasUncertainAffinityWith, Cnidaria]
-
A.
hasUncertainNature
Indicates that the nature, status, or characteristics of the relationship or situation are not clearly defined, known, or determined.
-
B.
hasUncertainty
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
C.
hasUncertainBoundary
Indicates that the boundary or extent of something is not clearly defined, fixed, or precisely known.
-
D.
hasUncertainNumber
Indicates that the associated quantity or count is not known precisely or cannot be determined with certainty.
-
E.
hasUncertainOrigin
Indicates that the origin or source of an entity, event, or information is unknown, unclear, or not reliably established.
- 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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8cc85b081908ee80db0e3b7df15 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:18 p.m.