Triple
T4088326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regge |
E87642
|
entity |
| Predicate | mouthRiver |
P4359
|
FINISHED |
| Object | Vecht |
E131160
|
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: Vecht | Statement: [Regge, mouthRiver, Vecht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vecht Context triple: [Regge, mouthRiver, Vecht]
-
A.
Vecht
The Vecht is a Dutch river known for flowing through the province of Utrecht past historic towns, castles, and scenic landscapes before reaching the IJsselmeer.
-
B.
Vecht
chosen
The Vecht is a river in the eastern Netherlands and western Germany known for flowing through the province of Overijssel and into the IJsselmeer.
-
C.
Rijnsweerd
Rijnsweerd is a neighborhood in Utrecht, Netherlands, known for encompassing the iconic modernist Rietveld Schröder House.
-
D.
Diksmuide
Diksmuide is a historic town in western Belgium known for its World War I battlefields and memorials, particularly the Yser Tower.
-
E.
Geervliet
Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefca899008190b5ada98bdb79639f |
completed | March 9, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f1ad4248190a01da6cbf73603c2 |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 9, 2026, 3:39 p.m.