Triple
T12267240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conditional GAN |
E292378
|
entity |
| Predicate | introducedBy |
P513
|
FINISHED |
| Object | Mehdi Mirza |
E428320
|
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: Mehdi Mirza | Statement: [Conditional GAN, introducedBy, Mehdi Mirza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mehdi Mirza Context triple: [Conditional GAN, introducedBy, Mehdi Mirza]
-
A.
Mehdi Mirza
chosen
Mehdi Mirza is a machine learning researcher known for his contributions to deep reinforcement learning and generative models.
-
B.
Saeed Jalili
Saeed Jalili is an Iranian conservative politician and diplomat known for serving as Iran’s chief nuclear negotiator and holding senior national security roles within the Islamic Republic.
-
C.
Mehdi Ali
Mehdi Ali is a businessman best known for leading Commodore International during its financially troubled final years in the early 1990s.
-
D.
Reza Abbasi
Reza Abbasi was a prominent Safavid-era Persian painter renowned for his elegant single-figure miniatures and influential role in the Isfahan school of art.
-
E.
Mehdi Hatamian
Mehdi Hatamian is an electrical engineer and technologist recognized for his influential contributions to high-speed integrated circuits and signal processing, for which he has received major industry honors.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cdd7b3c8190afd237cd9b633d4d |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e6799088190a5644267733ca2e5 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.