Triple
T16964363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulu cinema |
E411505
|
entity |
| Predicate | notableFilm |
P22
|
FINISHED |
| Object |
Dand
Dand is a Tulu-language film recognized as one of the notable works in Tulu cinema.
|
E1242543
|
NE FINISHED |
How this triple was built (4 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: Dand | Statement: [Tulu cinema, notableFilm, Dand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dand Context triple: [Tulu cinema, notableFilm, Dand]
-
A.
Dande
Dande is a town and municipality located in Angola’s Bengo Province.
-
B.
DARD
DARD is an organization focused on translating research findings into practical applications and real-world impact.
-
C.
Dang
Dang is a district in southwestern Nepal known for its fertile valleys, diverse ethnic communities, and role as a transport hub linking the Terai plains with the mid-hills.
-
D.
Doud
Doud is the maiden surname of Mamie Eisenhower, the First Lady of the United States during Dwight D. Eisenhower’s presidency.
-
E.
D.N.D.
D.N.D. is the standard legal abbreviation for the United States District Court for the District of North Dakota, a federal trial court within the Eighth Circuit.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dand Triple: [Tulu cinema, notableFilm, Dand]
Generated description
Dand is a Tulu-language film recognized as one of the notable works in Tulu cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dand Target entity description: Dand is a Tulu-language film recognized as one of the notable works in Tulu cinema.
-
A.
Dande
Dande is a town and municipality located in Angola’s Bengo Province.
-
B.
DARD
DARD is an organization focused on translating research findings into practical applications and real-world impact.
-
C.
Dang
Dang is a district in southwestern Nepal known for its fertile valleys, diverse ethnic communities, and role as a transport hub linking the Terai plains with the mid-hills.
-
D.
Doud
Doud is the maiden surname of Mamie Eisenhower, the First Lady of the United States during Dwight D. Eisenhower’s presidency.
-
E.
D.N.D.
D.N.D. is the standard legal abbreviation for the United States District Court for the District of North Dakota, a federal trial court within the Eighth Circuit.
- F. None of above. chosen
Provenance (5 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a2cda88190bd574a869f0e43e9 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d46cb56481908c2bc6648a12fbcf |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d4f1bfa48190903bedc43ed6db75 |
completed | May 10, 2026, 6:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d59b96108190a0e55f01529a0b64 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:31 a.m.