Triple
T93550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subrahmanyan Chandrasekhar |
E1879
|
entity |
| Predicate | relativeType |
P37
|
FINISHED |
| Object | nephew of C. V. Raman |
—
|
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: nephew of C. V. Raman | Statement: [Subrahmanyan Chandrasekhar, relativeType, nephew of C. V. Raman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeType Context triple: [Subrahmanyan Chandrasekhar, relativeType, nephew of C. V. Raman]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
notableRelative
Indicates that an entity has a relative who is notable or well-known, specifying that familial relationship.
-
C.
DSTRelation
Indicates a temporal relationship where one event, state, or timestamp is adjusted or interpreted according to Daylight Saving Time rules.
-
D.
subclassOf
Indicates that one class is a more specific type of another class, inheriting its characteristics as a subset of it.
-
E.
typeOfInheritance
Indicates the kind or pattern of inheritance by which a trait, property, or characteristic is passed from one entity or generation to another.
- 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a2512ef600819084d3c627f0d534f4 |
completed | Feb. 28, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_69a24eb9a5ac8190b1d1300e8c4e3606 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:07 a.m.