Triple
T499029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tariq Anwar |
E10358
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tariq Anwar |
E10358
|
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: Tariq Anwar | Statement: [Tariq Anwar, name, Tariq Anwar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tariq Anwar Context triple: [Tariq Anwar, name, Tariq Anwar]
-
A.
Tariq Anwar
chosen
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."
-
B.
M. Azhar
M. Azhar is an individual known for the honor of lighting the torch at the 1998 Commonwealth Games.
-
C.
Hafeez Jalandhari
Hafeez Jalandhari was a Pakistani poet best known for writing the lyrics of Pakistan’s national anthem.
-
D.
Hina Jilani
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.
-
E.
Oussama Khatib
Oussama Khatib is a prominent roboticist known for his pioneering work in robot motion planning, control, and human-robot interaction.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a481f1ee28819087e90028b89e877e |
completed | March 1, 2026, 6:14 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.