Triple
T65269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georg-August-Universität Göttingen |
E1298
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | GAU |
E1298
|
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: GAU | Statement: [Georg-August-Universität Göttingen, shortName, GAU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GAU Context triple: [Georg-August-Universität Göttingen, shortName, GAU]
-
A.
GAU
chosen
GAU is an abbreviation commonly used for the University of Göttingen, a major research university in Göttingen, Germany.
-
B.
GU
GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
-
C.
AMX
AMX is a Dutch stock market index that tracks the performance of mid-cap companies listed on Euronext Amsterdam.
-
D.
GA 85
GA 85 is a state highway in Georgia that runs generally south–north, connecting rural communities and suburbs to the Atlanta metropolitan area.
-
E.
AGSU
AGSU is the modern U.S. Army service uniform inspired by the World War II-era "pinks and greens" style, worn for everyday professional and ceremonial duties.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24ee6ba348190b00977285d74d8f5 |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25ab9477881908508e3130068bca3 |
completed | Feb. 28, 2026, 3:02 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.