Triple
T11747660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rendition |
E279324
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Mozaffar Karimi
Mozaffar Karimi is an actor known for his role in the film "Rendition."
|
E944756
|
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: Mozaffar Karimi | Statement: [Rendition, stars, Mozaffar Karimi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mozaffar Karimi Context triple: [Rendition, stars, Mozaffar Karimi]
-
A.
Rahmat Shoureshi
Rahmat Shoureshi is an engineer and academic leader known for co-founding Lattice Semiconductor and serving in senior roles at several universities.
-
B.
Mohsen Rezaee
Mohsen Rezaee is an Iranian politician and former senior military commander who served as the long-time chief of the Islamic Revolutionary Guard Corps during the Iran–Iraq War.
-
C.
Mohsen Foroughi
Mohsen Foroughi was a prominent Iranian architect known for designing significant public and institutional buildings in 20th-century Iran.
-
D.
Ezzatolah Entezami
Ezzatolah Entezami was a highly acclaimed Iranian film and stage actor, widely regarded as one of the most influential and respected figures in the history of Iranian cinema.
-
E.
Mohammad Mohaqiq
Mohammad Mohaqiq is an Afghan Hazara political leader and former mujahideen commander who has played a prominent role in Afghanistan’s post-Taliban politics.
- 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: Mozaffar Karimi Triple: [Rendition, stars, Mozaffar Karimi]
Generated description
Mozaffar Karimi is an actor known for his role in the film "Rendition."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mozaffar Karimi Target entity description: Mozaffar Karimi is an actor known for his role in the film "Rendition."
-
A.
Rahmat Shoureshi
Rahmat Shoureshi is an engineer and academic leader known for co-founding Lattice Semiconductor and serving in senior roles at several universities.
-
B.
Mohsen Rezaee
Mohsen Rezaee is an Iranian politician and former senior military commander who served as the long-time chief of the Islamic Revolutionary Guard Corps during the Iran–Iraq War.
-
C.
Mohsen Foroughi
Mohsen Foroughi was a prominent Iranian architect known for designing significant public and institutional buildings in 20th-century Iran.
-
D.
Ezzatolah Entezami
Ezzatolah Entezami was a highly acclaimed Iranian film and stage actor, widely regarded as one of the most influential and respected figures in the history of Iranian cinema.
-
E.
Mohammad Mohaqiq
Mohammad Mohaqiq is an Afghan Hazara political leader and former mujahideen commander who has played a prominent role in Afghanistan’s post-Taliban politics.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a50763a081908597da118bd0a64e |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f01a0492b48190b6f2e3cf36b4f537 |
completed | April 28, 2026, 2:23 a.m. |
| NEDg | Description generation | batch_69f0319520dc8190817c5e75ddb7d40b |
completed | April 28, 2026, 4:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f05ad36e4c8190b7239e5b33713369 |
completed | April 28, 2026, 6:59 a.m. |
Created at: April 8, 2026, 9:41 p.m.