Triple

T28256738
Position Surface form Disambiguated ID Type / Status
Subject Patuakhali Science and Technology University E712467 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Fisheries
The Faculty of Fisheries is an academic division specializing in fisheries science, aquaculture, and related marine and aquatic resource studies at Patuakhali Science and Technology University in Bangladesh.
 E1807444 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 Fisheries | Statement: [Patuakhali Science and Technology University, hasFaculty, Faculty of Fisheries]
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 Fisheries
Triple: [Patuakhali Science and Technology University, hasFaculty, Faculty of Fisheries]
Generated description
The Faculty of Fisheries is an academic division specializing in fisheries science, aquaculture, and related marine and aquatic resource studies at Patuakhali Science and Technology University in Bangladesh.

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_69efb5207eb08190827e4c34048030b1 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f643f4b1448190b5db963c0f041f9b completed May 2, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6dcc95c8190af9ea81d23f115de completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15e7a749e88190a6a38cac563a2931 completed May 26, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_6a15e8241cec819092154414d2bb5cad completed May 26, 2026, 6:36 p.m.
Created at: April 27, 2026, 11:08 p.m.