Triple
T994561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gigafactory Berlin-Brandenburg |
E21466
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Tesla Model Y |
E9723
|
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: Tesla Model Y | Statement: [Gigafactory Berlin-Brandenburg, product, Tesla Model Y]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tesla Model Y Context triple: [Gigafactory Berlin-Brandenburg, product, Tesla Model Y]
-
A.
Tesla Model Y
chosen
The Tesla Model Y is a compact all-electric crossover SUV known for its long range, advanced driver-assistance features, and minimalist high-tech interior.
-
B.
Tesla Model S
The Tesla Model S is a luxury all-electric sedan known for its long range, high performance, and role in popularizing mainstream electric vehicles.
-
C.
Tesla Model 3
The Tesla Model 3 is a mass-market electric sedan known for its long range, high performance, and role in popularizing electric vehicles worldwide.
-
D.
Tesla Model X
The Tesla Model X is an all-electric luxury SUV known for its falcon-wing rear doors, high performance, and advanced driver-assistance technology.
-
E.
Tesla Semi
The Tesla Semi is an all-electric Class 8 semi-truck designed to offer high efficiency, long range, and lower operating costs compared to traditional diesel trucks.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c75de88190bf7fec7a053f7a90 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3ba34c808190a745740c93cd520c |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.