Triple
T10468227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Girl on the Train (stage adaptation) |
E246858
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Megan Hipwell |
E180120
|
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: Megan Hipwell | Statement: [Girl on the Train (stage adaptation), hasCharacter, Megan Hipwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Hipwell Context triple: [Girl on the Train (stage adaptation), hasCharacter, Megan Hipwell]
-
A.
Megan Hipwell
chosen
Megan Hipwell is a troubled young woman whose mysterious disappearance drives the central suspense and emotional tension in the psychological thriller film "The Girl on the Train."
-
B.
Megan Gill
Megan Gill is a film editor best known for her work on major feature films, including the superhero movie "X-Men Origins: Wolverine."
-
C.
Megan Holley
Megan Holley is an American screenwriter best known for writing the indie dramedy film "Sunshine Cleaning."
-
D.
Amanda Hopkinson
Amanda Hopkinson is a British literary translator and academic known for translating major works of Spanish and Latin American literature into English.
-
E.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092ef810819093a4d1df83aeac09 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb028c0788190ae8d6750f2f9634e |
completed | April 14, 2026, 9:22 p.m. |
Created at: April 6, 2026, 12:20 p.m.