Triple
T1220898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LeBron James |
E26218
|
entity |
| Predicate | endorsedBrand |
P18857
|
FINISHED |
| Object | Sprite |
E85132
|
NE 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: Sprite | Statement: [LeBron James, endorsedBrand, Sprite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sprite Context triple: [LeBron James, endorsedBrand, Sprite]
-
A.
Sprite
chosen
Sprite is a popular lemon-lime flavored soft drink known for its crisp, caffeine-free taste and global presence.
-
B.
Pixel
Pixel is Google's flagship line of Android smartphones known for their clean software experience and advanced camera capabilities.
-
C.
SpriteKit
SpriteKit is Apple’s 2D game development framework designed for building high-performance, animated games and interactive content across its platforms.
-
D.
SPLASH
SPLASH is a major annual ACM conference focused on programming languages, software engineering, and related systems research.
-
E.
Loop
The Loop is Chicago’s central business district and downtown core, known for its dense cluster of skyscrapers, cultural institutions, and historic elevated train system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf169868819090cfab7e34c40c67 |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac832508c881908ea01e0b7c7e53eb |
completed | March 7, 2026, 7:57 p.m. |
Created at: March 1, 2026, 7:46 p.m.