Triple
T8289845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aero Snap |
E193865
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Snap |
E264026
|
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: Snap | Statement: [Aero Snap, alsoKnownAs, Snap]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snap Context triple: [Aero Snap, alsoKnownAs, Snap]
-
A.
Snap
chosen
Snap is a technology and social media company best known for creating Snapchat and developing camera-focused hardware and augmented reality products.
-
B.
Snap
Snap is the superhero alias used by Marvel Comics character Sam Wilson, better known as the Falcon and the second Captain America.
-
C.
Schnapp
Schnapp is the surname of American actor Noah Schnapp, best known for his role as Will Byers in the television series "Stranger Things."
-
D.
The Snap
The Snap is the catastrophic event in the Marvel Cinematic Universe where Thanos uses the Infinity Gauntlet to erase half of all life in the universe.
-
E.
Sno
Sno is a small mountain village in northeastern Georgia’s Kazbegi region, known for its traditional stone towers and scenic Caucasus landscapes.
- 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c99fdd48190a3f304237be609a0 |
completed | March 31, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68916c5481908c42f259298b0670 |
completed | April 1, 2026, 6:48 p.m. |
Created at: March 30, 2026, 5:52 p.m.