Triple

T34402465

Position	Surface form	Disambiguated ID	Type / Status
Subject	Claire Bennett (Cake)	`E883017`	entity
Predicate	hasFavoriteFood	`P22005`	FINISHED
Object	tres leches cake Tres leches cake is a rich, ultra-moist Latin American sponge cake soaked in a mixture of three milks and typically topped with whipped cream.	`E2095293`	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: tres leches cake | Statement: [Claire Bennett (Cake), hasFavoriteFood, tres leches cake]

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: tres leches cake
Triple: [Claire Bennett (Cake), hasFavoriteFood, tres leches cake]

Generated description

Tres leches cake is a rich, ultra-moist Latin American sponge cake soaked in a mixture of three milks and typically topped with whipped cream.

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

Target predicate: hasFavoriteFood
Context triple: [Claire Bennett (Cake), hasFavoriteFood, tres leches cake]

A. favoriteFood chosen
Indicates that one entity has a preferred or most liked food item in relation to another entity or context.
B. likesFood
Indicates that an entity has a positive preference for or enjoyment of a particular food.
C. hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
D. hasOwnDishes
Indicates that an entity possesses or is responsible for its own set of dishes, separate from those of others.
E. hasSpecialtyFood
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
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_69f349c1f2208190a09a489bb8b2719d`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69fd8ccbd4c88190b13aae0673b3c821`	completed	May 8, 2026, 7:12 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a370dcbeb9c8190bbf66e26331779b9`	completed	June 20, 2026, 10:01 p.m.
NEDg	Description generation	`batch_6a370e7f2e6c8190858406dcdcdaafb7`	completed	June 20, 2026, 10:04 p.m.
NED2	Entity disambiguation (via description)	`batch_6a370f0b3e5c8190a74b88ad1ba900ea`	completed	June 20, 2026, 10:07 p.m.
PD	Predicate disambiguation	`batch_69fd8ae2227c819089546f5c3629799e`	completed	May 8, 2026, 7:04 a.m.

Created at: May 1, 2026, 1:59 a.m.