Triple
T4344811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klaus Regling |
E97873
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Regling
Regling is a German surname most notably borne by economist Klaus Regling, former head of the European Stability Mechanism.
|
E434179
|
NE FINISHED |
How this triple was built (4 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: Regling | Statement: [Klaus Regling, familyName, Regling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Regling Context triple: [Klaus Regling, familyName, Regling]
-
A.
Regla
Regla is a coastal municipality of Havana, Cuba, known for its port, Afro-Cuban religious traditions, and location across the bay from Old Havana.
-
B.
Kural
Kural is the common short name for the Tirukkural, a classic Tamil text of concise couplets on ethics, governance, and love.
-
C.
Rule 32
Rule 32 is a provision of the Federal Rules of Criminal Procedure that governs procedures and requirements surrounding sentencing in federal criminal cases.
-
D.
Reg
Reg is a common shortened given name, typically derived from Reginald.
-
E.
Rule I
Rule I is the opening guideline in René Descartes’ unfinished work "Rules for the Direction of the Mind," where he begins outlining his method for achieving clear and certain knowledge.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Regling Triple: [Klaus Regling, familyName, Regling]
Generated description
Regling is a German surname most notably borne by economist Klaus Regling, former head of the European Stability Mechanism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Regling Target entity description: Regling is a German surname most notably borne by economist Klaus Regling, former head of the European Stability Mechanism.
-
A.
Regla
Regla is a coastal municipality of Havana, Cuba, known for its port, Afro-Cuban religious traditions, and location across the bay from Old Havana.
-
B.
Kural
Kural is the common short name for the Tirukkural, a classic Tamil text of concise couplets on ethics, governance, and love.
-
C.
Rule 32
Rule 32 is a provision of the Federal Rules of Criminal Procedure that governs procedures and requirements surrounding sentencing in federal criminal cases.
-
D.
Reg
Reg is a common shortened given name, typically derived from Reginald.
-
E.
Rule I
Rule I is the opening guideline in René Descartes’ unfinished work "Rules for the Direction of the Mind," where he begins outlining his method for achieving clear and certain knowledge.
- F. None of above. chosen
Provenance (5 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3518aa5cc8190b50f47b1070715fe |
completed | March 12, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dba5d2488190b23a0358ffc994fb |
completed | March 14, 2026, 10:05 p.m. |
| NEDg | Description generation | batch_69b5dc3d81a08190b29b633009fab4ff |
completed | March 14, 2026, 10:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5e04f356c81909e3f6f2c865e0f99 |
completed | March 14, 2026, 10:25 p.m. |
Created at: March 12, 2026, 11:15 p.m.