Triple

T33482970
Position Surface form Disambiguated ID Type / Status
Subject Princess Haifa bint Faisal Al Saud E857530 entity
Predicate affiliation P10 FINISHED
Object Zahra Breast Cancer Association
Zahra Breast Cancer Association is a Saudi non-profit organization dedicated to raising awareness, promoting early detection, and supporting patients affected by breast cancer.
E2053401 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: Zahra Breast Cancer Association | Statement: [Princess Haifa bint Faisal Al Saud, affiliation, Zahra Breast Cancer Association]
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: Zahra Breast Cancer Association
Triple: [Princess Haifa bint Faisal Al Saud, affiliation, Zahra Breast Cancer Association]
Generated description
Zahra Breast Cancer Association is a Saudi non-profit organization dedicated to raising awareness, promoting early detection, and supporting patients affected by breast cancer.

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_69f3497547608190a1a0f2365fb713ee completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e530e490819095ad1629a71ecd5a completed May 3, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595b3fd408190b3ae340c51a978ef completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a3598a1abb081909a3be50e398e67ea completed June 19, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a3599260a688190be69107b0600aa08 completed June 19, 2026, 7:31 p.m.
Created at: May 1, 2026, 1:38 a.m.