Triple

T23939722
Position Surface form Disambiguated ID Type / Status
Subject Semmelweis University E602747 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Health and Public Administration
The Faculty of Health and Public Administration is a division of Semmelweis University specializing in education and research in health sciences, health policy, and public administration.
 E1607909 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: Faculty of Health and Public Administration | Statement: [Semmelweis University, hasFaculty, Faculty of Health and Public Administration]
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: Faculty of Health and Public Administration
Triple: [Semmelweis University, hasFaculty, Faculty of Health and Public Administration]
Generated description
The Faculty of Health and Public Administration is a division of Semmelweis University specializing in education and research in health sciences, health policy, and public administration.

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_69e2953cf6e081909b8e25a10a52dddc completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1cfa40398819095e24521f3bf8622 completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f764c075c8190ada57a4b1ad63784 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 9:08 p.m.