Triple
T5259926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMa Overdensity |
E118797
|
entity |
| Predicate | hasUncertainNature |
P62578
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [CMa Overdensity, hasUncertainNature, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUncertainNature Context triple: [CMa Overdensity, hasUncertainNature, true]
-
A.
hasUncertainOrigin
Indicates that the origin or source of an entity, event, or information is unknown, unclear, or not reliably established.
-
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.
hasUncertainHistoricBasis
Indicates that the historical foundation or authenticity of the related fact, event, or relationship is doubtful, disputed, or not firmly established.
-
D.
hasUncertainVocabulary
Indicates that the relationship involves vocabulary whose meaning, usage, or interpretation is not clearly defined or is subject to doubt.
-
E.
hasUncertainBoundary
Indicates that the boundary or extent of something is not clearly defined, fixed, or precisely known.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcced6881909bdb7ac5471a37fe |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7bcabe58819096255672664513b1 |
completed | March 20, 2026, 4:54 p.m. |
Created at: March 20, 2026, 1:50 p.m.