Triple
T1915960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Technical University of Berlin |
E40017
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | CESAER |
E28802
|
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: CESAER | Statement: [Technical University of Berlin, memberOf, CESAER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CESAER Context triple: [Technical University of Berlin, memberOf, CESAER]
-
A.
CESAER
chosen
CESAER is a European association of leading universities of science and technology that collaborates to advance engineering education, research, and innovation.
-
B.
CESA
CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
-
C.
Cellese
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
-
D.
CESE
CESE is France’s Economic, Social and Environmental Council, a constitutional advisory body that represents civil society and provides expert opinions on public policy.
-
E.
CEA
CEA is the abbreviation for China Eastern Airlines, one of China's major state-owned carriers operating extensive domestic and international flight networks.
- 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.