Triple
T11965850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Creation |
E284787
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Adam
Adam is the first man in the biblical creation narrative, formed by God and placed in the Garden of Eden as the progenitor of humankind.
|
E20531
|
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: Adam | Statement: [The Creation, character, Adam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Context triple: [The Creation, character, Adam]
-
A.
Adam
Adam is a reclusive, centuries-old vampire musician and one of the two melancholic immortal lovers at the center of Jim Jarmusch’s film "Only Lovers Left Alive."
-
B.
Adam
Adam is a common surname of Scottish and English origin, borne by various notable individuals including architects, politicians, and artists.
-
C.
Adam
"Adam" is a 1983 American television film based on the true story of the kidnapping and murder of Adam Walsh, in which JoBeth Williams stars as the boy’s mother.
-
D.
Adam
Adam is a popular stochastic optimization algorithm widely used to train deep learning models by adaptively adjusting learning rates for each parameter.
-
E.
Adam
Adam is a widely used stochastic optimization algorithm in machine learning that combines ideas from momentum and adaptive learning rates to efficiently train deep neural networks.
- 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: Adam Triple: [The Creation, character, Adam]
Generated description
Adam is the first man in the biblical creation narrative, formed by God and placed in the Garden of Eden as the progenitor of humankind.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adam Target entity description: Adam is the first man in the biblical creation narrative, formed by God and placed in the Garden of Eden as the progenitor of humankind.
-
A.
Adam
chosen
Adam is the first human in Abrahamic religious traditions, whose disobedience in Eden is believed to have introduced sin into the human condition.
-
B.
Adam
Adam is a masculine given name of Hebrew origin, commonly used in many cultures and languages.
-
C.
Adam
Adam is a renowned sculpture by Auguste Rodin, notable for its expressive depiction of the biblical figure and housed in the Rodin Museum.
-
D.
Adam
Adam is a loyal, elderly servant in William Shakespeare’s comedy "As You Like It," known for his devotion and generosity toward Orlando.
-
E.
Adam
Adam is the reanimated creature who serves as the central monster figure in the horror film "I, Frankenstein."
- F. None of above.
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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903799f948190a5dc4d3822f3ff27 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f45952f69c8190a8c7f3c327ea1a63 |
completed | May 1, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69f45f89d5b08190a87312d96e61898a |
completed | May 1, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f464a5191881908e291943996169cb |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 8, 2026, 9:46 p.m.