Triple
T9997706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derek Charles |
E197243
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Kyle Charles
Kyle Charles is the son of Derek Charles, a character in the 2009 psychological thriller film "Obsessed."
|
E833700
|
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: Kyle Charles | Statement: [Derek Charles, hasChild, Kyle Charles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyle Charles Context triple: [Derek Charles, hasChild, Kyle Charles]
-
A.
Christopher Daniel Barnes
Christopher Daniel Barnes is an American actor best known for voicing Prince Eric in Disney’s "The Little Mermaid" and Peter Parker/Spider-Man in the 1990s animated series.
-
B.
Jace Darnell
Jace Darnell is a fictional character portrayed by actor Oliver Hudson in a television series.
-
C.
Jeremy Spenser
Jeremy Spenser is a British actor best known for his film and stage work in the 1950s and 1960s, including notable roles in classic British cinema.
-
D.
Phil Hardy
Phil Hardy was a British music industry journalist and author best known for his influential reference works on rock, pop, and film music.
-
E.
Michael Kube-McDowell
Michael Kube-McDowell is an American science fiction author known for his novels, short stories, and contributions to major franchises such as Star Wars.
- 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: Kyle Charles Triple: [Derek Charles, hasChild, Kyle Charles]
Generated description
Kyle Charles is the son of Derek Charles, a character in the 2009 psychological thriller film "Obsessed."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kyle Charles Target entity description: Kyle Charles is the son of Derek Charles, a character in the 2009 psychological thriller film "Obsessed."
-
A.
Christopher Daniel Barnes
Christopher Daniel Barnes is an American actor best known for voicing Prince Eric in Disney’s "The Little Mermaid" and Peter Parker/Spider-Man in the 1990s animated series.
-
B.
Jace Darnell
Jace Darnell is a fictional character portrayed by actor Oliver Hudson in a television series.
-
C.
Jeremy Spenser
Jeremy Spenser is a British actor best known for his film and stage work in the 1950s and 1960s, including notable roles in classic British cinema.
-
D.
Phil Hardy
Phil Hardy was a British music industry journalist and author best known for his influential reference works on rock, pop, and film music.
-
E.
Michael Kube-McDowell
Michael Kube-McDowell is an American science fiction author known for his novels, short stories, and contributions to major franchises such as Star Wars.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8aa1a881909879a694496f11a5 |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d258439fe88190b17da69f542ecf61 |
completed | April 5, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_69d259701e488190b288c9f523a1ec87 |
completed | April 5, 2026, 12:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d259da25e081909ac184f4fa80c57e |
completed | April 5, 2026, 12:47 p.m. |
Created at: March 30, 2026, 8:51 p.m.