Triple
T16481715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Snowmen |
E400333
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Dr Simeon
Dr Simeon is the human guise of the Great Intelligence and the main antagonist in the 2012 Doctor Who Christmas special "The Snowmen."
|
E1217406
|
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: Dr Simeon | Statement: [The Snowmen, featuresCharacter, Dr Simeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dr Simeon Context triple: [The Snowmen, featuresCharacter, Dr Simeon]
-
A.
Dr. Simon Neville
Dr. Simon Neville is a fictional doctor character portrayed by actor Michael E. Knight, known from American television drama.
-
B.
Simon Sifter
Simon Sifter is a supervisory FBI agent and team leader in the crime drama series "CSI: Cyber."
-
C.
Professor Simon Peach
Professor Simon Peach is a quirky and socially awkward computer expert who helps orchestrate the traffic-jam heist in the 1969 film "The Italian Job."
-
D.
Simon Dunsdon
Simon Dunsdon is a cinematographer known for his work on the animated film "Hotel Transylvania 3: Summer Vacation."
-
E.
Tom Simson
Tom Simson is a naïve but kind-hearted young prospector in Bret Harte’s short story “The Outcasts of Poker Flat,” whose innocence and loyalty contrast with the cynicism of the exiled gamblers and outcasts.
- 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: Dr Simeon Triple: [The Snowmen, featuresCharacter, Dr Simeon]
Generated description
Dr Simeon is the human guise of the Great Intelligence and the main antagonist in the 2012 Doctor Who Christmas special "The Snowmen."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dr Simeon Target entity description: Dr Simeon is the human guise of the Great Intelligence and the main antagonist in the 2012 Doctor Who Christmas special "The Snowmen."
-
A.
Dr. Simon Neville
Dr. Simon Neville is a fictional doctor character portrayed by actor Michael E. Knight, known from American television drama.
-
B.
Simon Sifter
Simon Sifter is a supervisory FBI agent and team leader in the crime drama series "CSI: Cyber."
-
C.
Professor Simon Peach
Professor Simon Peach is a quirky and socially awkward computer expert who helps orchestrate the traffic-jam heist in the 1969 film "The Italian Job."
-
D.
Simon Dunsdon
Simon Dunsdon is a cinematographer known for his work on the animated film "Hotel Transylvania 3: Summer Vacation."
-
E.
Tom Simson
Tom Simson is a naïve but kind-hearted young prospector in Bret Harte’s short story “The Outcasts of Poker Flat,” whose innocence and loyalty contrast with the cynicism of the exiled gamblers and outcasts.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e02b2c881909576a23bfbd3123c |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581ebe888190a331974473f1be1a |
completed | May 10, 2026, 10:04 a.m. |
| NEDg | Description generation | batch_6a0059473c088190a8c9fc757c0a3ef1 |
completed | May 10, 2026, 10:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a005a457868819096e21df6944de0ff |
completed | May 10, 2026, 10:13 a.m. |
Created at: April 10, 2026, 5:13 a.m.