Triple
T7235122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans Landa |
E155202
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Landa |
E334229
|
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: Landa | Statement: [Hans Landa, familyName, Landa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landa Context triple: [Hans Landa, familyName, Landa]
-
A.
Landa
chosen
Landa is a writing system historically used in parts of the Indian subcontinent, particularly in the Punjab region, for commercial and administrative purposes.
-
B.
Langella
Langella is an Italian-origin surname most notably borne by acclaimed American actor Frank Langella.
-
C.
Gonda
Gonda is a city in the Indian state of Uttar Pradesh, known for its agricultural economy and proximity to the Ghaghara River.
-
D.
Massandra
Massandra is a resort settlement near Yalta in Crimea, best known for its historic winery and palace.
-
E.
Balzar
Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea130e5c819087f74883760fe327 |
completed | March 27, 2026, 8:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc2d96588190bcf150cbfe4d015c |
completed | March 28, 2026, 12:40 p.m. |
Created at: March 27, 2026, 2:55 p.m.