Triple
T13132103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibn al-Shatir planetary model |
E311987
|
entity |
| Predicate | sharesMathematicalFeaturesWith |
P57352
|
FINISHED |
| Object | Copernicus’s planetary models |
—
|
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: Copernicus’s planetary models | Statement: [Ibn al-Shatir planetary model, sharesMathematicalFeaturesWith, Copernicus’s planetary models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesMathematicalFeaturesWith Context triple: [Ibn al-Shatir planetary model, sharesMathematicalFeaturesWith, Copernicus’s planetary models]
-
A.
sharesMathematicalStructureWith
chosen
Indicates that two entities exhibit the same or closely analogous underlying mathematical structure, such as isomorphism or structural equivalence.
-
B.
sharesDesignFeaturesWith
Indicates that two entities have similar or overlapping design characteristics, structures, or stylistic elements.
-
C.
sharesFeatureExtractor
Indicates that two or more models or components use the same feature extraction mechanism or module.
-
D.
hasMathematicalProperty
Indicates that one entity possesses or exhibits a specific mathematical property or characteristic.
-
E.
sharesArealFeaturesWith
Indicates that two entities possess similar or overlapping spatial or geographic characteristics.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b27a8c81909a92ab7be5d3a7e9 |
completed | April 10, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:08 p.m.