Triple
T32141762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burkert profile |
E820923
|
entity |
| Predicate | fits |
P173622
|
FINISHED |
| Object | rotation curves of dwarf galaxies |
—
|
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: rotation curves of dwarf galaxies | Statement: [Burkert profile, fits, rotation curves of dwarf galaxies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fits Context triple: [Burkert profile, fits, rotation curves of dwarf galaxies]
-
A.
fittedWith
Indicates that one entity is equipped, supplied, or provided with another entity as a component, feature, or accessory.
-
B.
suit
Indicates that one entity is appropriate, fitting, or satisfactory for another entity or a particular purpose or situation.
-
C.
mayNotFit
Indicates that one entity is unlikely or not expected to be suitable in size, capacity, or compatibility to be placed into, combined with, or used within another entity or context.
-
D.
typicalFit
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
-
E.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
- 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_69f3490520d081909b2f1271dab75faa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b9aed8c881908214b59cb895fa65 |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: May 1, 2026, 12:30 a.m.