Triple
T2752901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hertzsprung–Russell diagram |
E61028
|
entity |
| Predicate | showsCorrelationBetween |
P37
|
FINISHED |
| Object | stellar luminosity and temperature |
—
|
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: stellar luminosity and temperature | Statement: [Hertzsprung–Russell diagram, showsCorrelationBetween, stellar luminosity and temperature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showsCorrelationBetween Context triple: [Hertzsprung–Russell diagram, showsCorrelationBetween, stellar luminosity and temperature]
-
A.
hasCorrelativesSystem
Indicates that one entity possesses or employs a system of correlatives—structured, corresponding elements or forms that are systematically related to each other.
-
B.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
C.
relatedTest
Indicates that there exists some form of connection or association between one test and another.
-
D.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
sharesCauseWith
Indicates that two entities are associated with or arise from the same underlying cause or causal factor.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb6ed9c08190824d1866e198ef80 |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd82d005c81908a1ac7a1313c6d88 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.