Triple
T8825255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicholas Kaldor |
E209999
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kaldor |
E209999
|
NE 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: Kaldor | Statement: [Nicholas Kaldor, familyName, Kaldor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaldor Context triple: [Nicholas Kaldor, familyName, Kaldor]
-
A.
Kaldor
chosen
Kaldor is a surname most prominently associated with Nicholas Kaldor, a 20th-century economist known for his influential contributions to post-Keynesian economic theory.
-
B.
Eyring
Eyring is a surname most prominently associated with Henry Eyring, a renowned theoretical chemist known for his work on chemical reaction rates and transition state theory.
-
C.
Balkhausen
Balkhausen is a district within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Arend
Arend is a character in Joost van den Vondel’s historical play "Gijsbrecht van Aemstel," set in medieval Amsterdam.
-
E.
Arend
Arend was one of the ships in the early 18th-century Dutch expedition led by explorer Jacob Roggeveen, known for his discovery of Easter Island.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc60332d208190972a8b03fbd760ee |
completed | April 1, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_69cf894902588190adb60140c64561f6 |
completed | April 3, 2026, 9:32 a.m. |
Created at: March 30, 2026, 6:46 p.m.