Triple
T16183773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ira Khan |
E392747
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Junaid Khan |
E395042
|
NE FINISHED |
How this triple was built (2 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: Junaid Khan | Statement: [Ira Khan, sibling, Junaid Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Junaid Khan Context triple: [Ira Khan, sibling, Junaid Khan]
-
A.
Junaid Khan
chosen
Junaid Khan is the son of Indian actor Aamir Khan and has begun pursuing a career in acting and filmmaking.
-
B.
Tariq Anwar
Tariq Anwar is a British film editor known for his acclaimed work on numerous major films, including the Academy Award–winning drama "The King’s Speech."
-
C.
Khalid Farooqi
Khalid Farooqi is a military commander associated with the Afghan Islamist political and militant organization Hezb-e Islami Gulbuddin.
-
D.
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.
-
E.
Qais Khan
Qais Khan is an actor known for his role in the television series "Tehran."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205fc080819097858f36253fef7c |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f860ecc8190be904fa793968d89 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:02 a.m.