Triple
T3949480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Dexter |
E84827
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Dexter
Dexter is a surname most notably associated with English crime writer Colin Dexter, creator of the Inspector Morse series.
|
E401438
|
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: Dexter | Statement: [Colin Dexter, familyName, Dexter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dexter Context triple: [Colin Dexter, familyName, Dexter]
-
A.
Dexter
Dexter is the given name of Dexter Scott King, an American civil and animal rights activist and the son of Martin Luther King Jr.
-
B.
Dexter
Dexter is a critically acclaimed American crime drama television series that follows a Miami forensic blood-spatter analyst who leads a secret life as a vigilante serial killer.
-
C.
Dexter
Dexter is a small town in southeastern New Mexico, United States, known for its rural character and agricultural surroundings.
-
D.
Detective Riley
Detective Riley is a supporting police investigator character in the 2016 psychological thriller film "The Girl on the Train," involved in unraveling the central mystery.
-
E.
The Killing
The Killing is a 1956 film noir crime thriller directed by Stanley Kubrick about a meticulously planned racetrack heist that begins to unravel.
- 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: Dexter Triple: [Colin Dexter, familyName, Dexter]
Generated description
Dexter is a surname most notably associated with English crime writer Colin Dexter, creator of the Inspector Morse series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dexter Target entity description: Dexter is a surname most notably associated with English crime writer Colin Dexter, creator of the Inspector Morse series.
-
A.
Dexter
Dexter is the given name of Dexter Scott King, an American civil and animal rights activist and the son of Martin Luther King Jr.
-
B.
Dexter
Dexter is a critically acclaimed American crime drama television series that follows a Miami forensic blood-spatter analyst who leads a secret life as a vigilante serial killer.
-
C.
Dexter
Dexter is a small town in southeastern New Mexico, United States, known for its rural character and agricultural surroundings.
-
D.
Detective Riley
Detective Riley is a supporting police investigator character in the 2016 psychological thriller film "The Girl on the Train," involved in unraveling the central mystery.
-
E.
The Killing
The Killing is a 1956 film noir crime thriller directed by Stanley Kubrick about a meticulously planned racetrack heist that begins to unravel.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef910ecc08190a4fca89bcf063e0c |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5339feb4c8190ad96a5680cb5294e |
completed | March 14, 2026, 10:08 a.m. |
| NEDg | Description generation | batch_69b5346fb3648190b2b72e10179588ed |
completed | March 14, 2026, 10:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b534e98b8081909c2b71ff20fe0bb4 |
completed | March 14, 2026, 10:14 a.m. |
Created at: March 9, 2026, 3:30 p.m.