Triple
T13589356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bq |
E324650
|
entity |
| Predicate | relationToCurie |
P110186
|
FINISHED |
| Object | 1 Ci = 3.7×10^10 Bq |
—
|
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: 1 Ci = 3.7×10^10 Bq | Statement: [Bq, relationToCurie, 1 Ci = 3.7×10^10 Bq]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToCurie Context triple: [Bq, relationToCurie, 1 Ci = 3.7×10^10 Bq]
-
A.
relatedNamedEntity
Indicates that two entities are connected through a shared or associated proper name (e.g., person, organization, location, or other named entity).
-
B.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
geneticRelation
Indicates that two entities are connected through a hereditary or familial genetic relationship.
-
E.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.