Triple
T38558887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BNL |
E928020
|
entity |
| Predicate | basedOnFictionalEntity |
P92229
|
FINISHED |
| Object | Buy n Large |
—
|
NE NERFINISHED |
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: Buy n Large | Statement: [BNL, basedOnFictionalEntity, Buy n Large]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnFictionalEntity Context triple: [BNL, basedOnFictionalEntity, Buy n Large]
-
A.
usedByFictionalEntity
Indicates that something (e.g., an object, tool, or resource) is utilized or employed by a fictional entity.
-
B.
basedOnInFiction
chosen
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
C.
inspiredByFictionalCharacter
Indicates that an entity’s characteristics, actions, or creation are influenced or modeled after a specific fictional character.
-
D.
ownedByFictionalCharacter
Indicates that something is possessed or owned by a fictional (not real-world) character.
-
E.
usesFictionalCharacters
Indicates that one entity incorporates or employs fictional characters in relation to another entity (e.g., in its content, branding, or activities).
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff8ba3f8248190bbdf8e7ec2b35093 |
completed | May 9, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69ff8b41ba988190a7332e8317d10f09 |
completed | May 9, 2026, 7:30 p.m. |
Created at: May 3, 2026, 4:32 p.m.