Triple
T2675340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panzer division |
E56445
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Heer |
E9485
|
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: Heer | Statement: [Panzer division, usedBy, Heer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heer Context triple: [Panzer division, usedBy, Heer]
-
A.
Heer
chosen
The Heer was the land-based component of Nazi Germany’s armed forces, serving as its primary army during World War II.
-
B.
Henreid
Henreid is the surname of Paul Henreid, the Austrian-born actor and director best known for his roles in classic Hollywood films such as "Casablanca" and "Now, Voyager."
-
C.
Hein
Hein is a Dutch surname most notably borne by Piet Hein, a renowned 17th-century naval officer and folk hero of the Dutch Republic.
-
D.
Ritter
Ritter is the surname of Thelma Ritter, the acclaimed American character actress known for her sharp-tongued, working-class roles in mid-20th-century Hollywood films.
-
E.
König
König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9b3530c819093942cc985f814ef |
completed | March 7, 2026, 7:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa0638a9c8190b48ca5aa56eb66ff |
completed | March 10, 2026, 4:38 a.m. |
Created at: March 6, 2026, 9:54 p.m.