Triple
T3764027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Connery |
E82626
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Zardoz
Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
|
E386238
|
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: Zardoz | Statement: [Sean Connery, notableWork, Zardoz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zardoz Context triple: [Sean Connery, notableWork, Zardoz]
-
A.
Zezuru
Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
-
B.
Zagal
Zagal was an earlier Croatian airline company that operated prior to and was eventually succeeded by Croatia Airlines.
-
C.
Damogran
Damogran is a remote, sparsely inhabited planet in Douglas Adams' "The Hitchhiker's Guide to the Galaxy," notable as the secret construction site of the revolutionary starship Heart of Gold.
-
D.
Azara
Azara is a suburban locality on the outskirts of Guwahati in Assam, India, known for hosting the city's main international airport and related transport infrastructure.
-
E.
Ochtum
The Ochtum is a river in northwestern Germany that flows through Lower Saxony and Bremen before joining the Weser.
- 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: Zardoz Triple: [Sean Connery, notableWork, Zardoz]
Generated description
Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zardoz Target entity description: Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
-
A.
Zezuru
Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
-
B.
Zagal
Zagal was an earlier Croatian airline company that operated prior to and was eventually succeeded by Croatia Airlines.
-
C.
Damogran
Damogran is a remote, sparsely inhabited planet in Douglas Adams' "The Hitchhiker's Guide to the Galaxy," notable as the secret construction site of the revolutionary starship Heart of Gold.
-
D.
Azara
Azara is a suburban locality on the outskirts of Guwahati in Assam, India, known for hosting the city's main international airport and related transport infrastructure.
-
E.
Ochtum
The Ochtum is a river in northwestern Germany that flows through Lower Saxony and Bremen before joining the Weser.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbfd4be481908242c460a3f00c56 |
completed | March 8, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e51e54108190ab60e189cfbb0db0 |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e6a49ffc81908d6322b1ca6f6327 |
completed | March 14, 2026, 4:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e7311cc4819098926b36b94cae96 |
completed | March 14, 2026, 4:42 a.m. |
Created at: March 8, 2026, 3:35 p.m.