Triple
T35043259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Bubblegum |
E1011124
|
entity |
| Predicate | relationshipTypeWithFinn |
P206819
|
FINISHED |
| Object | former crush of Finn |
—
|
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: former crush of Finn | Statement: [Princess Bubblegum, relationshipTypeWithFinn, former crush of Finn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithFinn Context triple: [Princess Bubblegum, relationshipTypeWithFinn, former crush of Finn]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
fareRelationship
Indicates a relationship between entities based on the cost, pricing, or fare charged for a service or trip.
-
C.
financialRelationshipWith
Indicates a financial connection or association between entities, such as ownership, investment, funding, or other monetary ties.
-
D.
relationshipToSinis
Indicates a familial, social, or conceptual connection that one entity has to Sinis.
-
E.
relationToMLS
Indicates a relationship or association that an entity has with a specific MLS (Multiple Listing Service) system or record.
- 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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:01 p.m.