Triple
T6557395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zenne |
E152483
|
entity |
| Predicate | hasMajorTributary |
P415
|
FINISHED |
| Object | Hain |
E418435
|
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: Hain | Statement: [Zenne, hasMajorTributary, Hain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hain Context triple: [Zenne, hasMajorTributary, Hain]
-
A.
Haitink
Haitink is a Dutch surname most famously associated with Bernard Haitink, the renowned 20th-century conductor known for his interpretations of the symphonic repertoire.
-
B.
Haine
chosen
Haine is a river in western Europe that flows through northern France and southwestern Belgium, historically associated with the Hainaut region.
-
C.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
D.
Hau
Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
-
E.
Haya
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
- 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_69c688058d6881908c19b309cc55dbfa |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae1eb0888190a67b850ac2bca79c |
completed | March 27, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb862e308190af1028c76484a1ea |
completed | March 27, 2026, 6:25 p.m. |
Created at: March 27, 2026, 1:52 p.m.