Triple
T13316177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German XIV Panzer Corps |
E317193
|
entity |
| Predicate | militaryBranch |
P253
|
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: [German XIV Panzer Corps, militaryBranch, Heer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heer Context triple: [German XIV Panzer Corps, militaryBranch, 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.
Heris
Heris is a city in northwestern Iran known for its traditional handwoven carpets and rugs.
-
D.
Heriz
Heriz is a renowned carpet-weaving region in northwestern Iran, famous for its durable hand-knotted rugs featuring bold geometric medallion designs.
-
E.
Heers
Heers is a rural municipality in the Belgian province of Limburg, known for its agricultural landscape and historic villages.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990f9a384819085890e18255ee339 |
completed | April 11, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716e3617081909eea9989cf5e7b30 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:29 p.m.