Triple
T15534951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mini Mushroom |
E370316
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Peach |
E368639
|
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: Peach | Statement: [Mini Mushroom, usedBy, Peach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peach Context triple: [Mini Mushroom, usedBy, Peach]
-
A.
Peach
The peach is a sweet, juicy stone fruit with fuzzy skin, widely cultivated and celebrated in Georgia and other temperate regions.
-
B.
Peach
Peach is a friendly pink starfish character from Disney-Pixar’s Finding Nemo who appears in the The Seas with Nemo & Friends attraction at Epcot.
-
C.
Peach
chosen
Peach is a recurring princess character from Nintendo's Mario franchise, known for her distinctive pink dress and frequent appearances as a playable racer in the Mario Kart series.
-
D.
Peach
Peach is a common English surname borne by various individuals, including British military leader Stuart Peach.
-
E.
Peach
Peach is a Japanese low-cost airline brand operating domestic and international flights, known for its vibrant image and association with ANA Group.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442e327c8190b4b879c8a3cd38e3 |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d605b908190a18c63142c8bb854 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:06 a.m.