Triple
T12780955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asif Ali Zardari |
E305504
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Asif
Asif is a common male given name used in South Asian and Middle Eastern cultures, notably borne by Pakistani politician Asif Ali Zardari.
|
E1004905
|
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: Asif | Statement: [Asif Ali Zardari, givenName, Asif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asif Context triple: [Asif Ali Zardari, givenName, Asif]
-
A.
Ashfaq
Ashfaq is the given name of Ashfaqulla Khan, an Indian freedom fighter and revolutionary associated with the Hindustan Republican Association during the struggle against British rule.
-
B.
Arif
Arif is a masculine given name commonly used in various cultures, particularly in Arabic-speaking and Muslim-majority countries, meaning "knowledgeable" or "wise."
-
C.
Zafar
Zafar was an important ancient South Arabian city that served as the political and cultural center of the Himyarite Kingdom in what is now Yemen.
-
D.
Zafar
Zafar was the pen name of Bahadur Shah II, the last Mughal emperor of India and a noted Urdu poet.
-
E.
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."
- 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: Asif Triple: [Asif Ali Zardari, givenName, Asif]
Generated description
Asif is a common male given name used in South Asian and Middle Eastern cultures, notably borne by Pakistani politician Asif Ali Zardari.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asif Target entity description: Asif is a common male given name used in South Asian and Middle Eastern cultures, notably borne by Pakistani politician Asif Ali Zardari.
-
A.
Ashfaq
Ashfaq is the given name of Ashfaqulla Khan, an Indian freedom fighter and revolutionary associated with the Hindustan Republican Association during the struggle against British rule.
-
B.
Arif
Arif is a masculine given name commonly used in various cultures, particularly in Arabic-speaking and Muslim-majority countries, meaning "knowledgeable" or "wise."
-
C.
Zafar
Zafar was an important ancient South Arabian city that served as the political and cultural center of the Himyarite Kingdom in what is now Yemen.
-
D.
Zafar
Zafar was the pen name of Bahadur Shah II, the last Mughal emperor of India and a noted Urdu poet.
-
E.
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."
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5a5680819095dcd491486d23e7 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ebc75bc81908bad7fb06af674a9 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f68fb6790881908c1d6f53b54906a2 |
completed | May 2, 2026, 11:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f690c0bd208190bd1f04a9640ad1ce |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 9, 2026, 5:29 p.m.