Triple
T4135766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angel Soft |
E85150
|
entity |
| Predicate | hasProductVariant |
P455
|
FINISHED |
| Object | Angel Soft Mega Rolls |
E85150
|
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: Angel Soft Mega Rolls | Statement: [Angel Soft, hasProductVariant, Angel Soft Mega Rolls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angel Soft Mega Rolls Context triple: [Angel Soft, hasProductVariant, Angel Soft Mega Rolls]
-
A.
Angel Soft
chosen
Angel Soft is a popular American toilet paper brand known for its balance of softness, strength, and affordability.
-
B.
Donuts
Donuts is a highly influential 2006 instrumental hip-hop album by producer J Dilla, celebrated for its innovative sampling, emotional depth, and lasting impact on beat-making and underground hip-hop.
-
C.
Brolas
Brolas is a historic estate on the Isle of Mull in Scotland associated with Clan Maclean.
-
D.
Ambrosia
Ambrosia is a Thoroughbred racehorse known for competing on the track in professional horse racing events.
-
E.
Ambrosia
Ambrosia is a figure from Greek mythology, known as a daughter of the Titan Atlas.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0233009881909333375d597b58b6 |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576c75e5c8190acc4ee72cb574432 |
completed | March 14, 2026, 2:55 p.m. |
Created at: March 9, 2026, 3:43 p.m.