Triple
T10898419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ms. Marvel |
E257369
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Muneeba Khan
Muneeba Khan is Kamala Khan’s caring yet strict mother in Marvel’s Ms. Marvel series, grounding the story with her cultural traditions and family values.
|
E892978
|
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: Muneeba Khan | Statement: [Ms. Marvel, featuresCharacter, Muneeba Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muneeba Khan Context triple: [Ms. Marvel, featuresCharacter, Muneeba Khan]
-
A.
Moneeza Hashmi
Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
-
B.
Nasira Iqbal
Nasira Iqbal is a Pakistani jurist and former judge of the Lahore High Court, recognized as one of the country’s prominent female legal figures.
-
C.
Safia Akhtar
Safia Akhtar was the mother of renowned Indian lyricist and screenwriter Javed Akhtar and a member of a prominent literary family.
-
D.
Umaima Marvi
Umaima Marvi is the wife of educator and Khan Academy founder Sal Khan.
-
E.
Hina Jilani
Hina Jilani is a prominent Pakistani lawyer and human rights activist known for her pioneering work in women's rights, civil liberties, and international justice.
- 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: Muneeba Khan Triple: [Ms. Marvel, featuresCharacter, Muneeba Khan]
Generated description
Muneeba Khan is Kamala Khan’s caring yet strict mother in Marvel’s Ms. Marvel series, grounding the story with her cultural traditions and family values.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Muneeba Khan Target entity description: Muneeba Khan is Kamala Khan’s caring yet strict mother in Marvel’s Ms. Marvel series, grounding the story with her cultural traditions and family values.
-
A.
Moneeza Hashmi
Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
-
B.
Nasira Iqbal
Nasira Iqbal is a Pakistani jurist and former judge of the Lahore High Court, recognized as one of the country’s prominent female legal figures.
-
C.
Safia Akhtar
Safia Akhtar was the mother of renowned Indian lyricist and screenwriter Javed Akhtar and a member of a prominent literary family.
-
D.
Umaima Marvi
Umaima Marvi is the wife of educator and Khan Academy founder Sal Khan.
-
E.
Hina Jilani
Hina Jilani is a prominent Pakistani lawyer and human rights activist known for her pioneering work in women's rights, civil liberties, and international justice.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75d03a3fc81908df039b9b5ab9ca2 |
completed | April 9, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e15524ec5c8190a330ce5fc16dd11d |
completed | April 16, 2026, 9:31 p.m. |
| NEDg | Description generation | batch_69e17d3331788190a9ee03fc4c6ca191 |
completed | April 17, 2026, 12:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e1ff5b3d488190a545bee24381d01e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 8, 2026, 9:21 p.m.