Triple
T2450059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division for the Application of Research Discoveries |
E53680
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
DARD
DARD is an organization focused on translating research findings into practical applications and real-world impact.
|
E267500
|
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: DARD | Statement: [Division for the Application of Research Discoveries, hasAbbreviation, DARD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DARD Context triple: [Division for the Application of Research Discoveries, hasAbbreviation, DARD]
-
A.
Daha
Daha was a prominent historical city in East Java that served as the political and cultural center of the medieval Kediri Kingdom in Indonesia.
-
B.
Doud
Doud is the maiden surname of Mamie Eisenhower, the First Lady of the United States during Dwight D. Eisenhower’s presidency.
-
C.
DART
DART is the public transportation authority serving the Dallas–Fort Worth metropolitan area with buses, light rail, commuter rail, and paratransit services.
-
D.
DART
DART is an electrified suburban rail service that runs along the coast of Dublin and its surrounding areas, providing frequent commuter transport.
-
E.
Dern
Dern is a surname most prominently associated with American actor Bruce Dern and his family of performers.
- 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: DARD Triple: [Division for the Application of Research Discoveries, hasAbbreviation, DARD]
Generated description
DARD is an organization focused on translating research findings into practical applications and real-world impact.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DARD Target entity description: DARD is an organization focused on translating research findings into practical applications and real-world impact.
-
A.
Daha
Daha was a prominent historical city in East Java that served as the political and cultural center of the medieval Kediri Kingdom in Indonesia.
-
B.
Doud
Doud is the maiden surname of Mamie Eisenhower, the First Lady of the United States during Dwight D. Eisenhower’s presidency.
-
C.
DART
DART is the public transportation authority serving the Dallas–Fort Worth metropolitan area with buses, light rail, commuter rail, and paratransit services.
-
D.
DART
DART is an electrified suburban rail service that runs along the coast of Dublin and its surrounding areas, providing frequent commuter transport.
-
E.
Dern
Dern is a surname most prominently associated with American actor Bruce Dern and his family of performers.
- 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd0f2b8488190b1f6a86f0a9f83aa |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0c2a7b08190beb27f6a83208e5c |
completed | March 9, 2026, 4:09 p.m. |
| NEDg | Description generation | batch_69aef5de0e4c8190af460b7e2fb2a5eb |
completed | March 9, 2026, 4:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aef68a6a18819097876fea0120103b |
completed | March 9, 2026, 4:34 p.m. |
Created at: March 6, 2026, 9:43 p.m.