Triple
T1486156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Vilsmaier |
E29467
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Rama dama |
E169758
|
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: Rama dama | Statement: [Joseph Vilsmaier, directed, Rama dama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rama dama Context triple: [Joseph Vilsmaier, directed, Rama dama]
-
A.
Rama dama
chosen
Rama dama is a German drama film directed by Joseph Vilsmaier that portrays the hardships and rebuilding efforts in post-World War II Munich.
-
B.
Dama dama
Dama dama, commonly known as the fallow deer, is a medium-sized deer species native to Europe and widely introduced elsewhere, recognized for its spotted coat and palmate antlers in males.
-
C.
Rama Yantra
Rama Yantra is a large cylindrical astronomical instrument at Jantar Mantar in New Delhi used for measuring the altitude and azimuth of celestial bodies.
-
D.
Rama
Rama is a major Hindu deity and the virtuous prince-king of Ayodhya, revered as the seventh avatar of Vishnu and hero of the epic Ramayana.
-
E.
Naman
Naman is an endangered Oceanic language spoken by a small community in Vanuatu.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6a1d8448190b3c90bb82fd806fe |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1ca4c4e481909ea0ca76841454b1 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 8:12 p.m.