Triple
T23014845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grunewald |
E573002
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | AVUS |
—
|
NE NERFINISHED |
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: AVUS | Statement: [Grunewald, hasLandmark, AVUS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AVUS Context triple: [Grunewald, hasLandmark, AVUS]
-
A.
AVUS
chosen
AVUS is a historic German motor racing circuit and former public road in Berlin, renowned as one of the world’s earliest purpose-built race tracks.
-
B.
AVUM
AVUM is the liquid-propellant upper stage of the European Vega small-lift launch vehicle, responsible for precise orbital insertion and mission completion.
-
C.
Uesen
Uesen is a district or locality within the town of Achim in Lower Saxony, Germany.
-
D.
AUT
AUT is a leading Iranian engineering and technology university, widely recognized for its strong research output and rigorous academic programs.
-
E.
AUT
AUT is a major New Zealand university based in Auckland, known for its focus on applied research, innovation, and industry-aligned education.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e3c0e08190a7ac747b056ec3ca |
completed | April 29, 2026, 4:06 a.m. |
Created at: April 17, 2026, 3:51 p.m.