Triple
T29186546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rasa (aesthetic flavor) |
E739882
|
entity |
| Predicate | laterNumberOfRasas |
P62671
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Rasa (aesthetic flavor), laterNumberOfRasas, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterNumberOfRasas Context triple: [Rasa (aesthetic flavor), laterNumberOfRasas, 9]
-
A.
definesNumberOfRasas
chosen
Indicates that an entity specifies or determines the total number of rasas (distinct aesthetic or emotional flavors) associated with something.
-
B.
hasRasa
Indicates that one entity possesses, exhibits, or is characterized by a particular emotional flavor, aesthetic sentiment, or expressive quality (rasa) associated with another entity.
-
C.
laterNumber
Indicates that one number occurs or is positioned later than another in a specified ordering or sequence.
-
D.
rasa
Indicates that an entity is associated with or uses the Rasa conversational AI framework or platform.
-
E.
numberOfRukus
Indicates the quantity or count of distinct "Rukus" associated with or involved in a given entity or situation.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fe2f078c24819082ba396b56f02808 |
completed | May 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69fe228fe1988190baf3bb34897f3dbe |
completed | May 8, 2026, 5:51 p.m. |
Created at: April 28, 2026, noon