Triple

T25913326
Position Surface form Disambiguated ID Type / Status
Subject Hadid E652958 entity
Predicate hasNotableBearer P458 FINISHED
Object Mona Hadid
Mona Hadid is an American fashion model and social media personality, known as the younger sister of models Gigi and Bella Hadid.
E1755577 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: Mona Hadid | Statement: [Hadid, hasNotableBearer, Mona Hadid]
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: Mona Hadid
Triple: [Hadid, hasNotableBearer, Mona Hadid]
Generated description
Mona Hadid is an American fashion model and social media personality, known as the younger sister of models Gigi and Bella Hadid.

Provenance (5 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_69e7ab3e025c819086771607157f0015 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603c67f0c8190be8443cfa6e991b2 completed May 2, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123a87754481908b5cc45142315eba completed May 23, 2026, 11:38 p.m.
NEDg Description generation batch_6a123bbe49cc81908763b340636d7a60 completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123f9c03f881908e9cc1bc292b3e96 completed May 24, 2026, midnight
Created at: April 22, 2026, 8:30 a.m.