Triple
T17306782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Payman Maadi |
E420183
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | 6 Underground |
—
|
NE ONDG |
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: 6 Underground | Statement: [Payman Maadi, notableWork, 6 Underground]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 6 Underground Context triple: [Payman Maadi, notableWork, 6 Underground]
-
A.
6 Underground
6 Underground is a 2019 high-octane action film directed by Michael Bay, starring Ryan Reynolds as the leader of a covert vigilante squad that fakes their deaths to take down notorious criminals.
-
B.
Underground
Underground is a non-fiction book by Haruki Murakami that explores the 1995 Tokyo subway sarin gas attack through interviews with victims and members of the Aum Shinrikyo cult.
-
C.
Underground
Underground is a dystopian political thriller novel by Australian author Andrew McGahan that explores authoritarianism, surveillance, and resistance in a near-future Australia.
-
D.
Underground
Underground is a 1941 World War II espionage film in which Karen Verne plays a key role, contributing to her recognition as a German-born actress in Hollywood.
-
E.
Underground
Underground is the rapid transit system serving London and some surrounding areas, commonly known as the London Underground or the Tube.
- 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: 6 Underground Triple: [Payman Maadi, notableWork, 6 Underground]
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 6 Underground Target entity description: 6 Underground is a 2019 action thriller film directed by Michael Bay, starring Ryan Reynolds as the leader of a covert vigilante squad of presumed-dead operatives.
-
A.
6 Underground
chosen
6 Underground is a 2019 high-octane action film directed by Michael Bay, starring Ryan Reynolds as the leader of a covert vigilante squad that fakes their deaths to take down notorious criminals.
-
B.
Underground
Underground is a 1941 World War II espionage film in which Karen Verne plays a key role, contributing to her recognition as a German-born actress in Hollywood.
-
C.
Underground
Underground is a non-fiction book by Haruki Murakami that explores the 1995 Tokyo subway sarin gas attack through interviews with victims and members of the Aum Shinrikyo cult.
-
D.
Underground
Underground is the rapid transit system serving London and some surrounding areas, commonly known as the London Underground or the Tube.
-
E.
Underground
Underground is a dystopian political thriller novel by Australian author Andrew McGahan that explores authoritarianism, surveillance, and resistance in a near-future Australia.
- F. None of above.
Provenance (4 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4390005dc81908345ebb6dd970582 |
completed | April 19, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01954afb088190a92a0f32f901f13f |
completed | May 11, 2026, 8:37 a.m. |
| NEDg | Description generation | batch_6a01962ae4848190b2aad8e19bf6522f |
in_progress | May 11, 2026, 8:41 a.m. |
Created at: April 10, 2026, 5:43 a.m.