Triple
T5893311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best |
E131041
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Boxtel |
E131042
|
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: Boxtel | Statement: [Best, borderedBy, Boxtel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boxtel Context triple: [Best, borderedBy, Boxtel]
-
A.
Boxtel
chosen
Boxtel is a town and municipality in the southern Netherlands known for its historic center and location between the cities of Eindhoven and ’s-Hertogenbosch.
-
B.
Fitel
Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
-
C.
Anytos
Anytos is a figure from Greek mythology known primarily as a Titan or divine guardian associated with the Arcadian goddess Despoina.
-
D.
Volacom
Volacom is a company founded by Tesla co-founder and battery technology pioneer JB Straubel, likely focused on advanced engineering and sustainable technology solutions.
-
E.
Telefunken
Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036b5c68481909fdcba428238c74d |
completed | March 22, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b15146888190ab86eaf9e565ee28 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.