Triple
T16605734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DK |
E403443
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Diels |
E705125
|
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: Diels | Statement: [DK, hasComponent, Diels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diels Context triple: [DK, hasComponent, Diels]
-
A.
Diels
chosen
Diels is a German surname most notably associated with chemist Otto Diels, co-discoverer of the Diels–Alder reaction and Nobel laureate in Chemistry.
-
B.
Deitinger
Deitinger is the original surname of Italian-American actor Cesare Danova, known for his roles in mid-20th-century film and television.
-
C.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
D.
Lindlar
Lindlar is a municipality in western Germany’s North Rhine-Westphalia, known for its rural character and location within the hilly Bergisches Land region.
-
E.
Diller
Diller is a surname most prominently associated with American media executive and businessman Barry Diller.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36090cf388190b401c55230912104 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007daa9f7c8190a9540d9a7a6ca6fb |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.