Triple
T12715647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asma al-Assad |
E303831
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object |
Asma Akhras
Asma Akhras, better known as Asma al-Assad, is the British-born First Lady of Syria and wife of President Bashar al-Assad.
|
E997407
|
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: Asma Akhras | Statement: [Asma al-Assad, birthName, Asma Akhras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asma Akhras Context triple: [Asma al-Assad, birthName, Asma Akhras]
-
A.
Moneeza Hashmi
Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
-
B.
Safia Akhtar
Safia Akhtar was the mother of renowned Indian lyricist and screenwriter Javed Akhtar and a member of a prominent literary family.
-
C.
Fara Sherazi
Fara Sherazi is a fictional CIA analyst character from the television series "Homeland," portrayed by actress Nazanin Boniadi.
-
D.
Rasheda Ali
Rasheda Ali is an American author, public speaker, and advocate best known for her work on Parkinson’s disease awareness and as one of Muhammad Ali’s daughters.
-
E.
Farida Jalal
Farida Jalal is a veteran Indian film and television actress known for her versatile character roles and memorable performances across Hindi cinema since the 1960s.
- 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: Asma Akhras Triple: [Asma al-Assad, birthName, Asma Akhras]
Generated description
Asma Akhras, better known as Asma al-Assad, is the British-born First Lady of Syria and wife of President Bashar al-Assad.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asma Akhras Target entity description: Asma Akhras, better known as Asma al-Assad, is the British-born First Lady of Syria and wife of President Bashar al-Assad.
-
A.
Moneeza Hashmi
Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
-
B.
Safia Akhtar
Safia Akhtar was the mother of renowned Indian lyricist and screenwriter Javed Akhtar and a member of a prominent literary family.
-
C.
Fara Sherazi
Fara Sherazi is a fictional CIA analyst character from the television series "Homeland," portrayed by actress Nazanin Boniadi.
-
D.
Rasheda Ali
Rasheda Ali is an American author, public speaker, and advocate best known for her work on Parkinson’s disease awareness and as one of Muhammad Ali’s daughters.
-
E.
Farida Jalal
Farida Jalal is a veteran Indian film and television actress known for her versatile character roles and memorable performances across Hindi cinema since the 1960s.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9620bd6148190a2f50067a4c18c14 |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671bad5108190915d14c3ec3d2e27 |
completed | May 2, 2026, 9:50 p.m. |
| NEDg | Description generation | batch_69f67286f1b8819081db3da2f5c16daf |
completed | May 2, 2026, 9:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67323a724819092425cdb3a070b96 |
completed | May 2, 2026, 9:56 p.m. |
Created at: April 9, 2026, 5:23 p.m.