Triple
T5409276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Desai |
E120970
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Rahul Desai
Rahul Desai is a notable individual distinguished enough in his field or public life to be specifically recognized by name.
|
E517893
|
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: Rahul Desai | Statement: [Desai, hasNotableBearer, Rahul Desai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rahul Desai Context triple: [Desai, hasNotableBearer, Rahul Desai]
-
A.
Ashvin Desai
Ashvin Desai is known primarily as the husband of acclaimed Indian novelist Anita Desai.
-
B.
Rahul Bhatia
Rahul Bhatia is an Indian businessman best known as the co-founder and key architect of IndiGo’s rise into India’s largest low-cost airline.
-
C.
Deepak Nayyar
Deepak Nayyar is an Indian economist and academic known for his work on development economics and his leadership roles in major universities and international economic institutions.
-
D.
Ravi Iyer
Ravi Iyer is a prominent computer scientist recognized for his influential contributions to performance evaluation and computer systems, honored with the ACM SIGMETRICS Achievement Award.
-
E.
Amin Bhatia
Amin Bhatia is a Canadian composer and synthesist known for his cinematic electronic scores for film and television.
- 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: Rahul Desai Triple: [Desai, hasNotableBearer, Rahul Desai]
Generated description
Rahul Desai is a notable individual distinguished enough in his field or public life to be specifically recognized by name.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rahul Desai Target entity description: Rahul Desai is a notable individual distinguished enough in his field or public life to be specifically recognized by name.
-
A.
Ashvin Desai
Ashvin Desai is known primarily as the husband of acclaimed Indian novelist Anita Desai.
-
B.
Rahul Bhatia
Rahul Bhatia is an Indian businessman best known as the co-founder and key architect of IndiGo’s rise into India’s largest low-cost airline.
-
C.
Deepak Nayyar
Deepak Nayyar is an Indian economist and academic known for his work on development economics and his leadership roles in major universities and international economic institutions.
-
D.
Ravi Iyer
Ravi Iyer is a prominent computer scientist recognized for his influential contributions to performance evaluation and computer systems, honored with the ACM SIGMETRICS Achievement Award.
-
E.
Amin Bhatia
Amin Bhatia is a Canadian composer and synthesist known for his cinematic electronic scores for film and television.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8796a420819092c1771407cd1a5d |
completed | March 20, 2026, 5:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf339e02dc8190bb2ca6e0a0ef4621 |
completed | March 22, 2026, 12:11 a.m. |
| NEDg | Description generation | batch_69bf34b0e22c819091aefd30a5e5a13d |
completed | March 22, 2026, 12:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf35442cf481908053d3645e6e9968 |
completed | March 22, 2026, 12:18 a.m. |
Created at: March 20, 2026, 2:05 p.m.