Triple

T34792215

Position	Surface form	Disambiguated ID	Type / Status
Subject	Donkeyskin	`E1002976`	entity
Predicate	fairyTaleType	`P116843`	FINISHED
Object	Aarne–Thompson–Uther 510B Aarne–Thompson–Uther 510B is a folktale classification type encompassing “Donkeyskin”–style stories, in which a persecuted heroine flees incestuous or otherwise abusive marriage demands, disguises herself, and ultimately achieves recognition and a better fate.	`E2111255`	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: Aarne–Thompson–Uther 510B | Statement: [Donkeyskin, fairyTaleType, Aarne–Thompson–Uther 510B]

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: Aarne–Thompson–Uther 510B
Triple: [Donkeyskin, fairyTaleType, Aarne–Thompson–Uther 510B]

Generated description

Aarne–Thompson–Uther 510B is a folktale classification type encompassing “Donkeyskin”–style stories, in which a persecuted heroine flees incestuous or otherwise abusive marriage demands, disguises herself, and ultimately achieves recognition and a better fate.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: fairyTaleType
Context triple: [Donkeyskin, fairyTaleType, Aarne–Thompson–Uther 510B]

A. hasFolkTaleType chosen
Indicates that an entity (such as a story) is classified as belonging to a particular folk tale type or category.
B. hasFairyCharacters
Indicates that the subject includes or features characters that are fairies.
C. fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
D. treatmentOfCinderella
Indicates how one party behaves toward or deals with Cinderella.
E. folkloreCharacter
Indicates that one entity is a character originating from the traditional stories, myths, or legends associated with the other entity.
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_69f76db47d408190a24fc7164439ea2d`	completed	May 3, 2026, 3:45 p.m.
NER	Named-entity recognition	`batch_69f77ffa6b68819090257fed3802c239`	completed	May 3, 2026, 5:03 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37664ba7e48190b6a521e38ee28b3e`	completed	June 21, 2026, 4:19 a.m.
NEDg	Description generation	`batch_6a3767b4a3f4819092155966b9d94815`	completed	June 21, 2026, 4:25 a.m.
NED2	Entity disambiguation (via description)	`batch_6a376835564081909cf34121e4fc8975`	completed	June 21, 2026, 4:27 a.m.
PD	Predicate disambiguation	`batch_69f7795978c481909e152cd1bd02dd07`	completed	May 3, 2026, 4:35 p.m.

Created at: May 3, 2026, 3:59 p.m.