Triple
T6709134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eisenach |
E153084
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Sedan |
E100294
|
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: Sedan | Statement: [Eisenach, twinTown, Sedan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sedan Context triple: [Eisenach, twinTown, Sedan]
-
A.
Sedan
chosen
Sedan is a town in northeastern France best known as the site of major military engagements, including pivotal battles in both the Franco-Prussian War and World War II.
-
B.
SUV
SUV is the IATA airport code for Nausori International Airport, which serves Suva, the capital of Fiji.
-
C.
C-Class
The C-Class is a compact executive car line from Mercedes-Benz known for blending luxury, performance, and advanced technology in a smaller sedan, coupe, and wagon format.
-
D.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
E.
Gran Coupé
Gran Coupé is BMW’s four-door coupé body style, combining a sleek coupé silhouette with the practicality of additional doors and enhanced interior space.
- 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d105b49c8190932246a727e2c513 |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7008e6b308190a3d5db2bf4a469c4 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:06 p.m.