Triple

T10225677
Position Surface form Disambiguated ID Type / Status
Subject 9-1-1: Lone Star E243196 entity
Predicate character P662 FINISHED
Object Marjan Marwani
Marjan Marwani is a devout Muslim firefighter and paramedic known for her bravery, social media presence, and strong moral convictions on the TV series "9-1-1: Lone Star."
E852794 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: Marjan Marwani | Statement: [9-1-1: Lone Star, character, Marjan Marwani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marjan Marwani
Context triple: [9-1-1: Lone Star, character, Marjan Marwani]
  • A. Parvin Ardalan
    Parvin Ardalan is an Iranian feminist writer and human rights activist known for her leading role in Iran’s women’s rights movement.
  • B. Anna Kashfi
    Anna Kashfi was a British-Indian actress and the first wife of Hollywood star Marlon Brando.
  • C. Hedieh Tehrani
    Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
  • D. Malakeh Madar
    Malakeh Madar was the honorific title given to Tadj ol-Molouk, the queen mother of Iran during the Pahlavi dynasty.
  • E. Delaram Ali
    Delaram Ali is an Iranian women's rights activist known for her prominent role in Iran’s One Million Signatures Campaign challenging discriminatory laws against women.
  • 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: Marjan Marwani
Triple: [9-1-1: Lone Star, character, Marjan Marwani]
Generated description
Marjan Marwani is a devout Muslim firefighter and paramedic known for her bravery, social media presence, and strong moral convictions on the TV series "9-1-1: Lone Star."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marjan Marwani
Target entity description: Marjan Marwani is a devout Muslim firefighter and paramedic known for her bravery, social media presence, and strong moral convictions on the TV series "9-1-1: Lone Star."
  • A. Parvin Ardalan
    Parvin Ardalan is an Iranian feminist writer and human rights activist known for her leading role in Iran’s women’s rights movement.
  • B. Anna Kashfi
    Anna Kashfi was a British-Indian actress and the first wife of Hollywood star Marlon Brando.
  • C. Hedieh Tehrani
    Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
  • D. Malakeh Madar
    Malakeh Madar was the honorific title given to Tadj ol-Molouk, the queen mother of Iran during the Pahlavi dynasty.
  • E. Delaram Ali
    Delaram Ali is an Iranian women's rights activist known for her prominent role in Iran’s One Million Signatures Campaign challenging discriminatory laws against women.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d1f9cf6c81909a6b9e9b9d0a79fe completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f715bea881909da9d0749fa6420f completed April 9, 2026, 12:47 a.m.
NEDg Description generation batch_69d6fcaa16788190a4c7ef79a78febc6 completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd6d705c81908e469068937a79b3 completed April 9, 2026, 1:14 a.m.
Created at: April 6, 2026, 11:17 a.m.