Triple
T1716335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vixen |
E37297
|
entity |
| Predicate | listedWith |
P31874
|
FINISHED |
| Object | Donder |
E195056
|
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: Donder | Statement: [Vixen, listedWith, Donder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donder Context triple: [Vixen, listedWith, Donder]
-
A.
Donder
chosen
Donder is one of Santa Claus’s traditional reindeer, often listed alongside Dancer and the other members of his Christmas sleigh team.
-
B.
Ösel
Ösel is the historical German and Swedish name for Saaremaa, the largest island of Estonia in the Baltic Sea.
-
C.
Dueodde
Dueodde is a coastal village on the Danish island of Bornholm, renowned for its exceptionally fine white sand beaches and scenic dunes.
-
D.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
-
E.
Lebedus
Lebedus was an ancient Greek city of Ionia on the western coast of Asia Minor, known as a minor but strategically located coastal settlement involved in regional trade and politics.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abaffc4e5c81908ce0b9cfe833445e |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada97dfb1c819084e750a8550d3e82 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:30 p.m.