Triple
T22258000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheat Codes |
E550140
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Aquamarine |
—
|
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: Aquamarine | Statement: [Cheat Codes, hasTrack, Aquamarine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aquamarine Context triple: [Cheat Codes, hasTrack, Aquamarine]
-
A.
Aquamarine
Aquamarine is a blue to blue-green variety of the mineral beryl, prized as a gemstone for its clear, sea-colored appearance.
-
B.
Aquamarine
chosen
Aquamarine is a 2006 teen fantasy romantic comedy film about two best friends who discover a mermaid in a swimming pool.
-
C.
Aquamarine
Aquamarine is a small, high-ranking Homeworld Gem from *Steven Universe* known for her cold, condescending demeanor and ruthless efficiency in carrying out missions against the Crystal Gems.
-
D.
Sapphire
Sapphire is an American author best known for her novel "Push," which was adapted into the acclaimed film "Precious."
-
E.
Sapphire
Sapphire is a 1959 British crime drama film that explores racial tensions and prejudice in London through the investigation of a young woman's murder.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c4bff48190b4be83f5f7677ac8 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.