Triple
T14398224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney television movies |
E357004
|
entity |
| Predicate | notableTitle |
P22
|
FINISHED |
| Object |
Twitches
Twitches is a Disney Channel Original Movie about twin witches who discover their magical powers and destiny on their 21st birthday.
|
E1096674
|
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: Twitches | Statement: [Disney television movies, notableTitle, Twitches]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Twitches Context triple: [Disney television movies, notableTitle, Twitches]
-
A.
Tweants
Tweants is a Low Saxon regional dialect spoken in the Twente region of the eastern Netherlands.
-
B.
Tikkana
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
-
C.
Twist
"Twist" is a modern film adaptation of Charles Dickens' classic novel "Oliver Twist," featuring Rafferty Law in a leading role.
-
D.
Twist
"Twist" is a novel by Swedish author Klas Östergren, known for its intricate storytelling and exploration of contemporary Swedish society.
-
E.
Twist
Twist is a fictional surname most notably borne by Jack Twist, a central character in Annie Proulx’s short story and the film adaptation "Brokeback Mountain."
- 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: Twitches Triple: [Disney television movies, notableTitle, Twitches]
Generated description
Twitches is a Disney Channel Original Movie about twin witches who discover their magical powers and destiny on their 21st birthday.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Twitches Target entity description: Twitches is a Disney Channel Original Movie about twin witches who discover their magical powers and destiny on their 21st birthday.
-
A.
Tweants
Tweants is a Low Saxon regional dialect spoken in the Twente region of the eastern Netherlands.
-
B.
Tikkana
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
-
C.
Twist
"Twist" is a modern film adaptation of Charles Dickens' classic novel "Oliver Twist," featuring Rafferty Law in a leading role.
-
D.
Twist
"Twist" is a novel by Swedish author Klas Östergren, known for its intricate storytelling and exploration of contemporary Swedish society.
-
E.
Twist
Twist is a fictional surname most notably borne by Jack Twist, a central character in Annie Proulx’s short story and the film adaptation "Brokeback Mountain."
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9083f9d081908fe5c99655c410b3 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551cbdb08190a9ea53e607f2555b |
completed | May 8, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69fd55d90ed08190b6a0184715f39ff4 |
completed | May 8, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd565d32fc8190acc1e733537a23cb |
completed | May 8, 2026, 3:19 a.m. |
Created at: April 10, 2026, 1:17 a.m.