Triple

T37200250

Position	Surface form	Disambiguated ID	Type / Status
Subject	Allen E. Paulson College of Engineering and Computing	`E921711`	entity
Predicate	hasDepartment	`P35`	FINISHED
Object	Department of Civil Engineering and Construction The Department of Civil Engineering and Construction is an academic unit focused on educating students and conducting research in civil engineering and construction management disciplines.	`E2217834`	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: Department of Civil Engineering and Construction | Statement: [Allen E. Paulson College of Engineering and Computing, hasDepartment, Department of Civil Engineering and Construction]

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: Department of Civil Engineering and Construction
Triple: [Allen E. Paulson College of Engineering and Computing, hasDepartment, Department of Civil Engineering and Construction]

Generated description

The Department of Civil Engineering and Construction is an academic unit focused on educating students and conducting research in civil engineering and construction management disciplines.

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_69f76ea313a08190a54404cd1e47da90`	completed	May 3, 2026, 3:49 p.m.
NER	Named-entity recognition	`batch_69fb36446c1881909ac9f782a56f88e2`	completed	May 6, 2026, 12:38 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a40361b5c6c8190b9c51b1690f5d5e1`	completed	June 27, 2026, 8:44 p.m.
NEDg	Description generation	`batch_6a4037adc8108190bf35bf75d60ee259`	completed	June 27, 2026, 8:50 p.m.
NED2	Entity disambiguation (via description)	`batch_6a403905066c8190997af99b48b21a75`	completed	June 27, 2026, 8:56 p.m.

Created at: May 3, 2026, 4:15 p.m.