Triple
T5410679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambda-CDM model |
E121003
|
entity |
| Predicate | hasOpenIssues |
P42093
|
FINISHED |
| Object | Hubble tension |
—
|
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: Hubble tension | Statement: [Lambda-CDM model, hasOpenIssues, Hubble tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpenIssues Context triple: [Lambda-CDM model, hasOpenIssues, Hubble tension]
-
A.
numberOfIssues
Indicates the quantity of issues associated with a given entity or context.
-
B.
hasOpenQuestions
chosen
Indicates that there are unresolved or unanswered issues, problems, or inquiries associated with the referenced entity or context.
-
C.
hasTargetIssue
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
-
D.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
E.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
- 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_69bd463a41cc8190b32ff5af2b96ca93 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87985ee0819092a9a5cd6a948138 |
completed | March 20, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69bd8467e6b48190b9eaa9de67072e06 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:05 p.m.