Triple
T1915956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Technical University of Berlin |
E40017
|
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: [Technical University of Berlin, memberOf, TU9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TU9 Context triple: [Technical University of Berlin, 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.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
C.
ZTU
ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
TNUA
TNUA is an academic association or network that includes Nagoya University among its member institutions.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1e517e8819086e4bf5a305aeb25 |
completed | March 7, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3da81308190a49844a8ac2997da |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:35 p.m.