Triple
T8631854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heinkel He 219 |
E204421
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Uhu |
E204421
|
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: Uhu | Statement: [Heinkel He 219, nickname, Uhu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uhu Context triple: [Heinkel He 219, nickname, Uhu]
-
A.
Uhu
chosen
Uhu was the nickname of the Heinkel He 219, a German World War II night fighter aircraft notable for its advanced radar and effectiveness against Allied bombers.
-
B.
Tinte
Tinte is a small village in the Dutch province of South Holland, known for its rural character and annual local festivities.
-
C.
Goop
Goop is a lifestyle and wellness brand known for its high-end products, health advice, and often controversial alternative medicine recommendations.
-
D.
Essie
Essie is a popular nail polish and nail care brand known for its wide range of fashion-forward colors and salon-quality formulas.
-
E.
Garnier
Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47417e9c819099739ae901449308 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebc13073c8190ad6e92b8f7161739 |
completed | April 2, 2026, 6:57 p.m. |
Created at: March 30, 2026, 6:27 p.m.