Triple
T21363988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Land van Heusden |
E526859
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Haarsteeg |
—
|
NE NERFINISHED |
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: Haarsteeg | Statement: [Land van Heusden, contains, Haarsteeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haarsteeg Context triple: [Land van Heusden, contains, Haarsteeg]
-
A.
Haarstrang
Haarstrang is a low mountain range in North Rhine-Westphalia, Germany, forming a natural boundary between the Soest plain and the higher Sauerland region.
-
B.
Haacht
Haacht is a municipality in the Flemish Brabant province of Belgium, known for its local brewery and semi-rural character near the city of Leuven.
-
C.
Haaren
chosen
Haaren is a village and former municipality in the Dutch province of North Brabant.
-
D.
Haasgat
Haasgat is a fossil-bearing cave site in South Africa known for its valuable paleoanthropological and paleontological remains.
-
E.
Halske
Halske is a German surname most notably associated with Johann Georg Halske, co-founder of the electrical engineering company Siemens & Halske.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b06d6dcc8190b438d3c2e620578c |
completed | April 22, 2026, 11:26 a.m. |
Created at: April 16, 2026, 5:08 p.m.