Triple
T14287080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Enough and Time |
E354202
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Missy |
E90859
|
NE FINISHED |
How this triple was built (2 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: Missy | Statement: [World Enough and Time, featuresCharacter, Missy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Missy Context triple: [World Enough and Time, featuresCharacter, Missy]
-
A.
Missy
chosen
Missy is the female incarnation of the Master, a recurring Time Lord villain and nemesis of the Doctor in the British science fiction series Doctor Who.
-
B.
Missy
Missy is a small Swiss municipality located in the canton of Vaud.
-
C.
Missi
Missi is an American actress and singer known for her comedic and character roles in film and television, including appearances in "Dodgeball," "Galaxy Quest," and "Charlie and the Chocolate Factory."
-
D.
Missy Gold
Missy Gold is an American former child actress best known for her role as Katie Gatling on the 1980s sitcom "Benson."
-
E.
Misti
Misti is a prominent, snow-capped stratovolcano overlooking the city of Arequipa in southern Peru.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de698023288190b1d705235c2b2ca3 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1c4d988190b595e6a33ef96c28 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:11 a.m.