Triple

T2034862
Position Surface form Disambiguated ID Type / Status
Subject Shirin Ebadi E44600 entity
Predicate givenName P17 FINISHED
Object Shirin
Shirin is a feminine given name of Persian origin, widely used in Iran and other Persian-influenced cultures.
 E229793 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: Shirin | Statement: [Shirin Ebadi, givenName, Shirin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shirin
Context triple: [Shirin Ebadi, givenName, Shirin]
  • A. Gulnare
    Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
  • B. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • C. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • D. Sana'i
    Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
  • E. Behdini
    Behdini is a Northern Kurdish (Kurmanji) dialect spoken primarily by Kurdish communities in and around the Dohuk region of Iraqi Kurdistan.
  • 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: Shirin
Triple: [Shirin Ebadi, givenName, Shirin]
Generated description
Shirin is a feminine given name of Persian origin, widely used in Iran and other Persian-influenced cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shirin
Target entity description: Shirin is a feminine given name of Persian origin, widely used in Iran and other Persian-influenced cultures.
  • A. Gulnare
    Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
  • B. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • C. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • D. Sana'i
    Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
  • E. Behdini
    Behdini is a Northern Kurdish (Kurmanji) dialect spoken primarily by Kurdish communities in and around the Dohuk region of Iraqi Kurdistan.
  • 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_69a889159ec481908f9e4472d9f480c7 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb93387488190ac9d8d2746451f2e completed March 7, 2026, 5:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1ff03d3c8190adef0224aac989bd completed March 9, 2026, 1:18 a.m.
NEDg Description generation batch_69ae2092c3ac8190b2f1f3e9c980f40a completed March 9, 2026, 1:21 a.m.
NED2 Entity disambiguation (via description) batch_69ae21c757c88190a151e01ee0825d85 completed March 9, 2026, 1:26 a.m.
Created at: March 4, 2026, 7:39 p.m.