Triple
T14840190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wakenitz |
E348940
|
entity |
| Predicate | tributaryOf |
P415
|
FINISHED |
| Object | Trave |
E228990
|
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: Trave | Statement: [Wakenitz, tributaryOf, Trave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trave Context triple: [Wakenitz, tributaryOf, Trave]
-
A.
Trave
chosen
The Trave is a river in northern Germany that flows through the state of Schleswig-Holstein to the Baltic Sea, notably passing through the city of Lübeck.
-
B.
TRV
TRV is the stock ticker symbol for The Travelers Companies, a major U.S.-based insurance provider known for its property and casualty insurance products.
-
C.
Travers
Travers is a former municipality in the canton of Neuchâtel, Switzerland, now incorporated into the larger municipality of Val-de-Travers.
-
D.
Travers
Travers is a fictional English surname most notably borne by Aunt Dahlia in P. G. Wodehouse’s Jeeves and Wooster stories.
-
E.
Travers
Travers is the given name of the British actor Henry Travers, best known for his role as Clarence the angel in the classic film "It's a Wonderful Life."
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded28e40f08190b309d8ac6404d2fc |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72a6b4388190b83bdecb217b9b18 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 10, 2026, 1:53 a.m.