Triple
T16447564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohammad Khodabanda |
E399470
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Zaynab Begum
Zaynab Begum was a Safavid royal consort and influential political figure as the wife of Shah Mohammad Khodabanda in 16th-century Iran.
|
E1217595
|
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: Zaynab Begum | Statement: [Mohammad Khodabanda, spouse, Zaynab Begum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaynab Begum Context triple: [Mohammad Khodabanda, spouse, Zaynab Begum]
-
A.
Maryam Begum
Maryam Begum was a Safavid royal woman best known as the mother of Shah Sultan Husayn, the last Safavid ruler of Iran.
-
B.
Zulaikha Begum
Zulaikha Begum was the mother of Maulana Abul Kalam Azad, the prominent Indian freedom fighter, Islamic scholar, and first Minister of Education of independent India.
-
C.
Khadija Zaman Begum
Khadija Zaman Begum was a consort of Tipu Sultan, the 18th-century ruler of the Kingdom of Mysore in southern India.
-
D.
Fatima Begum
Fatima Begum was a consort of Tipu Sultan, the 18th-century ruler of the Kingdom of Mysore in southern India.
-
E.
Wafa Begum
Wafa Begum was a queen consort of the Durrani Empire as the wife of Afghan ruler Shuja Shah Durrani.
- 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: Zaynab Begum Triple: [Mohammad Khodabanda, spouse, Zaynab Begum]
Generated description
Zaynab Begum was a Safavid royal consort and influential political figure as the wife of Shah Mohammad Khodabanda in 16th-century Iran.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zaynab Begum Target entity description: Zaynab Begum was a Safavid royal consort and influential political figure as the wife of Shah Mohammad Khodabanda in 16th-century Iran.
-
A.
Maryam Begum
Maryam Begum was a Safavid royal woman best known as the mother of Shah Sultan Husayn, the last Safavid ruler of Iran.
-
B.
Zulaikha Begum
Zulaikha Begum was the mother of Maulana Abul Kalam Azad, the prominent Indian freedom fighter, Islamic scholar, and first Minister of Education of independent India.
-
C.
Khadija Zaman Begum
Khadija Zaman Begum was a consort of Tipu Sultan, the 18th-century ruler of the Kingdom of Mysore in southern India.
-
D.
Fatima Begum
Fatima Begum was a consort of Tipu Sultan, the 18th-century ruler of the Kingdom of Mysore in southern India.
-
E.
Wafa Begum
Wafa Begum was a queen consort of the Durrani Empire as the wife of Afghan ruler Shuja Shah Durrani.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cddfc3c8190919b49f74b7e8e1a |
completed | April 18, 2026, 7:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0060746c308190b67ff7c4646e10de |
completed | May 10, 2026, 10:39 a.m. |
| NEDg | Description generation | batch_6a00614185008190bf4abe2443222225 |
completed | May 10, 2026, 10:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0061b833548190a56a32e634757419 |
completed | May 10, 2026, 10:45 a.m. |
Created at: April 10, 2026, 5:10 a.m.