Triple
T9459152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Keyes |
E228096
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Keyes
Keyes is the surname of American author Daniel Keyes, best known for writing the science fiction classic "Flowers for Algernon."
|
E801368
|
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: Keyes | Statement: [Daniel Keyes, familyName, Keyes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keyes Context triple: [Daniel Keyes, familyName, Keyes]
-
A.
Keyes
Keyes is a small unincorporated community located in Stanislaus County in California’s Central Valley.
-
B.
Klyuchi
Klyuchi is a rural settlement in Russia’s Kamchatka Peninsula known primarily as the closest community to the active Klyuchevskoy volcano.
-
C.
The Key
"The Key" is a song by British rock musician Ian Hunter, known for its introspective lyrics and melodic rock style.
-
D.
Kes
Kes is a 1969 British drama film directed by Ken Loach, widely acclaimed for its realistic portrayal of a working-class boy in Northern England who finds solace in training a kestrel.
-
E.
Kes
Kes is an Ocampa crew member on Star Trek: Voyager, known for her short lifespan, strong empathic and telepathic abilities, and close relationships with Neelix and the Doctor.
- 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: Keyes Triple: [Daniel Keyes, familyName, Keyes]
Generated description
Keyes is the surname of American author Daniel Keyes, best known for writing the science fiction classic "Flowers for Algernon."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Keyes Target entity description: Keyes is the surname of American author Daniel Keyes, best known for writing the science fiction classic "Flowers for Algernon."
-
A.
Keyes
Keyes is a small unincorporated community located in Stanislaus County in California’s Central Valley.
-
B.
Klyuchi
Klyuchi is a rural settlement in Russia’s Kamchatka Peninsula known primarily as the closest community to the active Klyuchevskoy volcano.
-
C.
The Key
"The Key" is a song by British rock musician Ian Hunter, known for its introspective lyrics and melodic rock style.
-
D.
Kes
Kes is a 1969 British drama film directed by Ken Loach, widely acclaimed for its realistic portrayal of a working-class boy in Northern England who finds solace in training a kestrel.
-
E.
Kes
Kes is an Ocampa crew member on Star Trek: Voyager, known for her short lifespan, strong empathic and telepathic abilities, and close relationships with Neelix and the Doctor.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fc916348190aeb3874a89071677 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1228d7a488190b537db256f386786 |
completed | April 4, 2026, 2:39 p.m. |
| NEDg | Description generation | batch_69d12395841c8190857de8a50ab6345c |
completed | April 4, 2026, 2:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1275bcbd88190a5742a9cf802425a |
completed | April 4, 2026, 2:59 p.m. |
Created at: March 30, 2026, 7:52 p.m.