Triple
T13283843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atypical |
E316388
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Zahid Raja
Zahid Raja is a charming, socially awkward, and humorous young man on the Netflix series "Atypical," known for being Sam Gardner’s loyal friend and coworker at the electronics store.
|
E1030420
|
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: Zahid Raja | Statement: [Atypical, character, Zahid Raja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zahid Raja Context triple: [Atypical, character, Zahid Raja]
-
A.
Qais Khan
Qais Khan is an actor known for his role in the television series "Tehran."
-
B.
Zafar Saifullah
Zafar Saifullah was a senior Indian civil servant who served as Cabinet Secretary and held several key administrative positions in the Government of India.
-
C.
Junaid Khan
Junaid Khan is the son of Indian actor Aamir Khan and has begun pursuing a career in acting and filmmaking.
-
D.
Muhammad Azam
Muhammad Azam, better known as Azam Shah, was a Mughal prince who briefly ruled as emperor of the Mughal Empire in the early 18th century.
-
E.
Jahangir Khan Tareen
Jahangir Khan Tareen is a prominent Pakistani businessman and politician known for his influential role in national politics and major involvement in the country’s sugar industry.
- 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: Zahid Raja Triple: [Atypical, character, Zahid Raja]
Generated description
Zahid Raja is a charming, socially awkward, and humorous young man on the Netflix series "Atypical," known for being Sam Gardner’s loyal friend and coworker at the electronics store.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zahid Raja Target entity description: Zahid Raja is a charming, socially awkward, and humorous young man on the Netflix series "Atypical," known for being Sam Gardner’s loyal friend and coworker at the electronics store.
-
A.
Qais Khan
Qais Khan is an actor known for his role in the television series "Tehran."
-
B.
Zafar Saifullah
Zafar Saifullah was a senior Indian civil servant who served as Cabinet Secretary and held several key administrative positions in the Government of India.
-
C.
Junaid Khan
Junaid Khan is the son of Indian actor Aamir Khan and has begun pursuing a career in acting and filmmaking.
-
D.
Muhammad Azam
Muhammad Azam, better known as Azam Shah, was a Mughal prince who briefly ruled as emperor of the Mughal Empire in the early 18th century.
-
E.
Jahangir Khan Tareen
Jahangir Khan Tareen is a prominent Pakistani businessman and politician known for his influential role in national politics and major involvement in the country’s sugar industry.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99047531c819087aa6406de1ddc82 |
completed | April 11, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a5a98488190804a97a052741377 |
completed | May 3, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_69f70b117c588190bb81ff53664cac4a |
completed | May 3, 2026, 8:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70c04da34819091e01db25741674e |
completed | May 3, 2026, 8:49 a.m. |
Created at: April 9, 2026, 9:27 p.m.