Triple
T6828205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Auster |
E157067
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
4 3 2 1
4 3 2 1 is a novel by American author Paul Auster that explores themes of chance, identity, and storytelling through an experimental, metafictional narrative structure.
|
E622135
|
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: 4 3 2 1 | Statement: [Paul Auster, notableWork, 4 3 2 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 4 3 2 1 Context triple: [Paul Auster, notableWork, 4 3 2 1]
-
A.
One, Two, Three
One, Two, Three is a 1961 fast-paced Cold War comedy film set in West Berlin, known for its rapid-fire dialogue and satirical take on East–West tensions.
-
B.
One by One
One by One is a 2002 rock album by Foo Fighters known for its heavier sound and hit singles like "All My Life" and "Times Like These."
-
C.
One by One
"One by One" is a song recorded by the American R&B/rock and roll vocal group The Coasters.
-
D.
4 the Cause
4 the Cause was a 1990s American R&B group best known internationally for their hit cover of Ben E. King’s “Stand by Me.”
-
E.
All 4
All 4 was the former name of Channel 4’s on-demand streaming service in the United Kingdom, offering catch-up and box-set content across its TV brands.
- 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: 4 3 2 1 Triple: [Paul Auster, notableWork, 4 3 2 1]
Generated description
4 3 2 1 is a novel by American author Paul Auster that explores themes of chance, identity, and storytelling through an experimental, metafictional narrative structure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 4 3 2 1 Target entity description: 4 3 2 1 is a novel by American author Paul Auster that explores themes of chance, identity, and storytelling through an experimental, metafictional narrative structure.
-
A.
One, Two, Three
One, Two, Three is a 1961 fast-paced Cold War comedy film set in West Berlin, known for its rapid-fire dialogue and satirical take on East–West tensions.
-
B.
One by One
One by One is a 2002 rock album by Foo Fighters known for its heavier sound and hit singles like "All My Life" and "Times Like These."
-
C.
One by One
"One by One" is a song recorded by the American R&B/rock and roll vocal group The Coasters.
-
D.
4 the Cause
4 the Cause was a 1990s American R&B group best known internationally for their hit cover of Ben E. King’s “Stand by Me.”
-
E.
All 4
All 4 was the former name of Channel 4’s on-demand streaming service in the United Kingdom, offering catch-up and box-set content across its TV brands.
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6254bd88190a2a424537c2c12e2 |
completed | March 27, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723f49bdc8190af39b34dbaf3f0c9 |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c724d7f0308190abb494ea663ceeb9 |
completed | March 28, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c72568866c8190bf88a02e566d5c3a |
completed | March 28, 2026, 12:48 a.m. |
Created at: March 27, 2026, 2:18 p.m.