Triple
T1549300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dara Khosrowshahi |
E33050
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
|
E175757
|
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: Dara | Statement: [Dara Khosrowshahi, givenName, Dara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dara Context triple: [Dara Khosrowshahi, givenName, Dara]
-
A.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
B.
Durkan
Durkan is a surname most notably associated with Jenny Durkan, the former mayor of Seattle and an American attorney and politician.
-
C.
Guna
Guna is a city in the central Indian state of Madhya Pradesh known as an important regional administrative and commercial center.
-
D.
Ledaal
Ledaal is a historic manor house in Stavanger, Norway, that has served as a royal residence and cultural landmark.
-
E.
Beni
Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
- 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: Dara Triple: [Dara Khosrowshahi, givenName, Dara]
Generated description
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dara Target entity description: Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
-
A.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
B.
Durkan
Durkan is a surname most notably associated with Jenny Durkan, the former mayor of Seattle and an American attorney and politician.
-
C.
Guna
Guna is a city in the central Indian state of Madhya Pradesh known as an important regional administrative and commercial center.
-
D.
Ledaal
Ledaal is a historic manor house in Stavanger, Norway, that has served as a royal residence and cultural landmark.
-
E.
Beni
Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90857bfb48190a2d66a601d228b72 |
completed | March 5, 2026, 4:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad30a29ae88190ab1b2ca97b8ed09c |
completed | March 8, 2026, 8:17 a.m. |
| NEDg | Description generation | batch_69ad3196e92481909bd09e6c765a9698 |
completed | March 8, 2026, 8:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad32391ed881909826a80a90f18cb4 |
completed | March 8, 2026, 8:24 a.m. |
Created at: March 4, 2026, 7:26 p.m.