Triple
T16944515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagoya Municipal Subway |
E411033
|
entity |
| Predicate | hasRollingStockType |
P1305
|
FINISHED |
| Object | N3000-1 series |
E1242089
|
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: N3000-1 series | Statement: [Nagoya Municipal Subway, hasRollingStockType, N3000-1 series]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: N3000-1 series Context triple: [Nagoya Municipal Subway, hasRollingStockType, N3000-1 series]
-
A.
N3000 series
chosen
The N3000 series is a type of electric multiple unit train used on the Nagoya Municipal Subway in Japan.
-
B.
Latitude 3000 series
The Latitude 3000 series is Dell’s line of budget-friendly business laptops designed to offer essential performance, durability, and manageability for professional and educational use.
-
C.
6050H series
The 6050H series is a type of electric multiple unit train used for passenger services on the Nagoya Municipal Subway in Japan.
-
D.
ND-5000
The ND-5000 is a more advanced, next-generation model in the ND series, offering improved performance and capabilities over its predecessor.
-
E.
B5000 series
The B5000 series was a line of innovative mainframe computers from Burroughs, notable for their early use of stack-based architecture and high-level language support.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfb08da88190b07c32652bbc1534 |
completed | April 18, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d46036108190a3ed8cb9f80c47fb |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.