Triple
T8371056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panzer Group von Kleist |
E197454
|
entity |
| Predicate | branch |
P889
|
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 Group von Kleist, branch, Heer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heer Context triple: [Panzer Group von Kleist, branch, Heer]
-
A.
Heer
Heer is the tragic heroine of the classic Punjabi romantic epic "Heer Ranjha," renowned as a symbol of eternal love and devotion.
-
B.
Heer
chosen
The Heer was the land-based component of Nazi Germany’s armed forces, serving as its primary army during World War II.
-
C.
Heriz
Heriz is a renowned carpet-weaving region in northwestern Iran, famous for its durable hand-knotted rugs featuring bold geometric medallion designs.
-
D.
Heers
Heers is a rural municipality in the Belgian province of Limburg, known for its agricultural landscape and historic villages.
-
E.
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."
- 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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80a509dc81909e0ea4c66b21d84f |
completed | March 31, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc79752b48190933ea644a59f2305 |
completed | April 2, 2026, 1:34 a.m. |
Created at: March 30, 2026, 6:01 p.m.