Triple
T24355913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Gentleman’s Guide to Love and Murder |
E613921
|
entity |
| Predicate | familyNameInPlot |
P107260
|
FINISHED |
| Object |
D’Ysquith
D’Ysquith is the aristocratic family whose members are systematically targeted for inheritance in the darkly comic musical "A Gentleman’s Guide to Love and Murder."
|
E1630512
|
NE FINISHED |
How this triple was built (3 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: D’Ysquith | Statement: [A Gentleman’s Guide to Love and Murder, familyNameInPlot, D’Ysquith]
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: D’Ysquith Triple: [A Gentleman’s Guide to Love and Murder, familyNameInPlot, D’Ysquith]
Generated description
D’Ysquith is the aristocratic family whose members are systematically targeted for inheritance in the darkly comic musical "A Gentleman’s Guide to Love and Murder."
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyNameInPlot Context triple: [A Gentleman’s Guide to Love and Murder, familyNameInPlot, D’Ysquith]
-
A.
familySurnameInStory
chosen
Indicates that a particular family surname appears within the narrative or context of a given story.
-
B.
familyNameIn
Indicates that an entity has a specified family name (surname) in a particular language or cultural context.
-
C.
familyNameOfMembers
Indicates that the specified family name is shared by the members of a given group or family.
-
D.
familyName
Indicates that one entity is the family (last) name associated with another entity (typically a person).
-
E.
protagonistFamilyName
Indicates that the subject is the family name (surname) of the story’s protagonist.
- F. None of above.
Provenance (6 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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29348b3448190aa0e87c0eb891d66 |
completed | April 29, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fd66a0b1481908928c6c437a75825 |
completed | May 22, 2026, 4:07 a.m. |
| NEDg | Description generation | batch_6a0fd726b1b08190a13ac712e0d40a7a |
completed | May 22, 2026, 4:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fd852ca8c81909bf1731a342d4a6d |
completed | May 22, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2 a.m.