Triple
T6817793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Stuttgart |
E156810
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | TU9 |
E126174
|
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: TU9 | Statement: [University of Stuttgart, memberOf, TU9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TU9 Context triple: [University of Stuttgart, memberOf, TU9]
-
A.
TU9
chosen
TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
-
B.
TÜ
TÜ is the official vehicle registration code used on license plates for the district of Tübingen in Germany.
-
C.
Tu
The Tu are a Mongolic-speaking ethnic minority in northwestern China, known for their Tibetan Buddhist traditions and distinctive agrarian culture in Qinghai and Gansu provinces.
-
D.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
E.
TU
TU is the common English abbreviation for Tohoku University, a leading national research university in Sendai, Japan.
- 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d355b52081909f037cec76bdccf6 |
completed | March 27, 2026, 6:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723e458d881909fcea55915514eb1 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:17 p.m.