Triple
T6679712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tübingen |
E151945
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
TÜ
TÜ is the official vehicle registration code used on license plates for the district of Tübingen in Germany.
|
E611657
|
NE FINISHED |
How this triple was built (4 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: TÜ | Statement: [Tübingen, vehicleRegistrationCode, TÜ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TÜ Context triple: [Tübingen, vehicleRegistrationCode, TÜ]
-
A.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
B.
TU
TU is the common English abbreviation for Tohoku University, a leading national research university in Sendai, Japan.
-
C.
TU9
TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
-
D.
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.
-
E.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TÜ Triple: [Tübingen, vehicleRegistrationCode, TÜ]
Generated description
TÜ is the official vehicle registration code used on license plates for the district of Tübingen in Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TÜ Target entity description: TÜ is the official vehicle registration code used on license plates for the district of Tübingen in Germany.
-
A.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
B.
TU
TU is the common English abbreviation for Tohoku University, a leading national research university in Sendai, Japan.
-
C.
TU9
TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
-
D.
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.
-
E.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
- F. None of above. chosen
Provenance (5 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b11df8d88190bf19fcb4e7a0bdb3 |
completed | March 27, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a9fda4819096d4bd3e8133cecb |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8b1e1f48190bc9058a8a21a4a62 |
completed | March 27, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f9441d74819098f0639a29fdeb5e |
completed | March 27, 2026, 9:40 p.m. |
Created at: March 27, 2026, 2:03 p.m.