Triple
T13662582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alzette River |
E327035
|
entity |
| Predicate | lengthInLuxembourg |
P111051
|
FINISHED |
| Object | majority of total length |
—
|
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: majority of total length | Statement: [Alzette River, lengthInLuxembourg, majority of total length]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthInLuxembourg Context triple: [Alzette River, lengthInLuxembourg, majority of total length]
-
A.
lengthInFrance
Indicates that the specified length or duration applies specifically within the context of France (e.g., under French conditions, jurisdiction, or territory).
-
B.
populationRankInLuxembourg
Indicates the relative position of a place in Luxembourg when ordered by the size of its population.
-
C.
distanceToLuxembourgCityKilometers
Indicates the physical distance, measured in kilometers, between the given entity and Luxembourg City.
-
D.
lengthInGermany
Indicates the extent or duration of something measured specifically within the geographic or jurisdictional boundaries of Germany.
-
E.
reasonForAccessionInLuxembourg
Indicates the reason or basis for which an entity obtained the right to be registered, operate, or be recognized in Luxembourg.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.