Triple
T7796649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziauddin |
E180314
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Zia |
E180314
|
NE FINISHED |
How this triple was built (2 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: Zia | Statement: [Ziauddin, shortForm, Zia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zia Context triple: [Ziauddin, shortForm, Zia]
-
A.
Zia
Zia is a feminine given name used in various cultures, often meaning "light" or "splendor."
-
B.
Ziauddin
chosen
Ziauddin is a male given name commonly used in Muslim communities, particularly in South Asia and the Middle East.
-
C.
Zia Mohyeddin
Zia Mohyeddin was a renowned Pakistani-British actor, producer, and television host known for his distinguished stage and screen performances and his iconic Urdu literary recitations.
-
D.
Azam Khan
Azam Khan is an Indian politician and founding member of the Samajwadi Party, known for his long tenure as a legislator from Uttar Pradesh and his influential role in state politics.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae982c3b48190a35afe655fb20d55 |
completed | March 30, 2026, 9:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a18014c8190be64130bfb856e10 |
completed | March 31, 2026, 5:22 a.m. |
Created at: March 30, 2026, 4:32 p.m.