Triple
T12132871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haldemann |
E288976
|
entity |
| Predicate | hasTypicalGeographicOrigin |
P103556
|
FINISHED |
| Object | German-speaking regions |
—
|
LITERAL 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: German-speaking regions | Statement: [Haldemann, hasTypicalGeographicOrigin, German-speaking regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalGeographicOrigin Context triple: [Haldemann, hasTypicalGeographicOrigin, German-speaking regions]
-
A.
speciesOrigin
Indicates the place, environment, or source from which a species originally arose or evolved.
-
B.
hasCountryOfOriginToponym
Indicates that something has a place name (toponym) specifying the country from which it originates.
-
C.
typicalOriginMetroArea
Indicates the metropolitan area from which something or someone most commonly originates or is typically sourced.
-
D.
allegedBirthRegion
Indicates the region where an entity is claimed or reported to have been born, without asserting that this birthplace is verified as fact.
-
E.
originalHomeland
Indicates the place or region that is considered the ancestral or earliest homeland of an entity.
- F. None of above. chosen
Provenance (4 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9183ec1008190b437b7d5e1f52830 |
completed | April 10, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:49 p.m.