Triple
T16487316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prime Minister of Luxembourg |
E400478
|
entity |
| Predicate | officeHoldersTitleInLuxembourgish |
P123716
|
FINISHED |
| Object | Premierminister vum Lëtzebuerg |
—
|
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: Premierminister vum Lëtzebuerg | Statement: [Prime Minister of Luxembourg, officeHoldersTitleInLuxembourgish, Premierminister vum Lëtzebuerg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHoldersTitleInLuxembourgish Context triple: [Prime Minister of Luxembourg, officeHoldersTitleInLuxembourgish, Premierminister vum Lëtzebuerg]
-
A.
officeHoldersTitleInFrench
Indicates that an office holder’s official title is expressed in the French language.
-
B.
officeHoldersTitleInDutch
Indicates that an office holder’s official title is given in the Dutch language.
-
C.
officeHolderTitleInLatin
Indicates that the specified office holder’s title is expressed in its Latin-language form.
-
D.
officeHolderTitleInGerman
Indicates the official title or designation of an office holder expressed in the German language.
-
E.
officeHoldersBelongTo
Indicates that designated office holders are affiliated with or part of a particular organization, institution, or administrative unit.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e078d0c8190a5698a5eb9df22d4 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:13 a.m.