Triple
T10506229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AGHS Legal Aid Cell |
E247792
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | Hina Jilani |
E49415
|
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: Hina Jilani | Statement: [AGHS Legal Aid Cell, hasNotableMember, Hina Jilani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hina Jilani Context triple: [AGHS Legal Aid Cell, hasNotableMember, Hina Jilani]
-
A.
Hina Jilani
chosen
Hina Jilani is a prominent Pakistani lawyer and human rights activist known for her pioneering work in women's rights, civil liberties, and international justice.
-
B.
Intizar Hussain
Intizar Hussain was a prominent Pakistani writer and critic renowned for his Urdu short stories and novels that blend tradition, memory, and modernist narrative techniques.
-
C.
Nasira Iqbal
Nasira Iqbal is a Pakistani jurist and former judge of the Lahore High Court, recognized as one of the country’s prominent female legal figures.
-
D.
Umaima Marvi
Umaima Marvi is the wife of educator and Khan Academy founder Sal Khan.
-
E.
Moneeza Hashmi
Moneeza Hashmi is a Pakistani television producer and media professional known for her contributions to public broadcasting and cultural programming.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509a07c908190bf0e3e5d480b306d |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b13f4fc8190863d6e1aa7da5733 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:26 p.m.