Triple
T14934202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E372347
|
entity |
| Predicate | hasLanguageOfUse |
P207
|
FINISHED |
| Object | German language |
E9053
|
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: German language | Statement: [George, hasLanguageOfUse, German language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: German language Context triple: [George, hasLanguageOfUse, German language]
-
A.
German
German refers to a person belonging to the ethnic group native to Germany, typically associated with the German language and culture.
-
B.
German
chosen
German is a West Germanic language widely spoken in Central Europe and used as an official language in several countries, including Germany, Austria, Switzerland, and Luxembourg.
-
C.
GRMN
GRMN is a high-performance sub-brand of Toyota’s Gazoo Racing division, offering limited-run, track-focused versions of select Toyota models.
-
D.
Deutsche
Deutsche is a German term meaning "German," commonly used in the names of German institutions, companies, and cultural entities.
-
E.
German ICE
The German ICE (InterCity Express) is Germany’s high-speed train system, known for its fast, comfortable long-distance rail service and advanced engineering.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded646a0808190ba5c0c91bde011c5 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e8c8d188190b027f14256b0ce01 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:37 a.m.