Triple
T7089340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Fire tablet |
E165151
|
entity |
| Predicate | hasModel |
P2390
|
FINISHED |
| Object | Fire 7 |
E640017
|
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: Fire 7 | Statement: [Amazon Fire tablet, hasModel, Fire 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fire 7 Context triple: [Amazon Fire tablet, hasModel, Fire 7]
-
A.
Fire 7
chosen
Fire 7 is Amazon’s compact, budget-friendly 7-inch Fire tablet designed for basic media consumption, reading, and everyday apps.
-
B.
Firepower
Firepower is a Transformers character known as a powerful Autobot warrior distinguished by his heavy weaponry and combat capabilities.
-
C.
Bigfire
Bigfire is a rustic, American-style restaurant at Universal CityWalk Orlando known for its open-fire cooking and wood-smoked dishes.
-
D.
Firewall
"Firewall" is a 2006 techno-thriller film starring Harrison Ford as a security expert forced to rob the bank he protects after his family is taken hostage.
-
E.
Fire Max 11
Fire Max 11 is a large-screen Amazon Fire tablet model designed for media consumption, productivity, and entertainment.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e52ec0348190ac090c2fee3edfb8 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c924ac88190a237d2e0ac505d51 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:41 p.m.