Triple
T16056397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deadly Impact |
E389491
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Alexander Vesha
Alexander Vesha is a screenwriter best known for his work on the action film "Deadly Impact."
|
E1191961
|
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: Alexander Vesha | Statement: [Deadly Impact, screenwriter, Alexander Vesha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexander Vesha Context triple: [Deadly Impact, screenwriter, Alexander Vesha]
-
A.
Konstantin
Konstantin is a masculine given name of Latin origin, widely used in Slavic and other European cultures, meaning “steadfast” or “constant.”
-
B.
Vladimir
Vladimir is a common Russian male given name of Slavic origin, historically associated with rulers and notably borne by Russian president Vladimir Putin.
-
C.
Vladimir
Vladimir is a historic Russian city east of Moscow, known as one of the medieval capitals of Russia and a key center of the Golden Ring.
-
D.
Alexander V
Alexander V was a Pisan-line antipope during the Western Schism who briefly claimed the papacy in the early 15th century amid rival papal claimants.
-
E.
Vasil
Vasil is a masculine given name, commonly used in Slavic and Balkan countries, that is related to names like Vasyl and Basil.
- 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: Alexander Vesha Triple: [Deadly Impact, screenwriter, Alexander Vesha]
Generated description
Alexander Vesha is a screenwriter best known for his work on the action film "Deadly Impact."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alexander Vesha Target entity description: Alexander Vesha is a screenwriter best known for his work on the action film "Deadly Impact."
-
A.
Konstantin
Konstantin is a masculine given name of Latin origin, widely used in Slavic and other European cultures, meaning “steadfast” or “constant.”
-
B.
Vladimir
Vladimir is a common Russian male given name of Slavic origin, historically associated with rulers and notably borne by Russian president Vladimir Putin.
-
C.
Vladimir
Vladimir is a historic Russian city east of Moscow, known as one of the medieval capitals of Russia and a key center of the Golden Ring.
-
D.
Alexander V
Alexander V was a Pisan-line antipope during the Western Schism who briefly claimed the papacy in the early 15th century amid rival papal claimants.
-
E.
Vasil
Vasil is a masculine given name, commonly used in Slavic and Balkan countries, that is related to names like Vasyl and Basil.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837579488190964ca004c2eb01c4 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbe49bd0819088e25de082184133 |
completed | May 10, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69ffde320f748190b7abf6ad4cc81ed9 |
completed | May 10, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffdec2dd18819092882485ae2baabe |
completed | May 10, 2026, 1:26 a.m. |
Created at: April 10, 2026, 4:56 a.m.