Triple

T35460428
Position Surface form Disambiguated ID Type / Status
Subject Houston Community College System E1024898 entity
Predicate hasCampus P116 FINISHED
Object HCC Coleman College for Health Sciences
HCC Coleman College for Health Sciences is a specialized Houston-based institution focused on training students for careers in healthcare and allied health professions.
E2141886 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: HCC Coleman College for Health Sciences | Statement: [Houston Community College System, hasCampus, HCC Coleman College for Health Sciences]
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: HCC Coleman College for Health Sciences
Triple: [Houston Community College System, hasCampus, HCC Coleman College for Health Sciences]
Generated description
HCC Coleman College for Health Sciences is a specialized Houston-based institution focused on training students for careers in healthcare and allied health professions.

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_69f76df92f108190817222e520e22268 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7966cfff48190801e836e0a7b652d completed May 3, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38402ee590819080564606e37d2a24 completed June 21, 2026, 7:49 p.m.
NEDg Description generation batch_6a3841005e4c8190b34e152079613853 completed June 21, 2026, 7:52 p.m.
NED2 Entity disambiguation (via description) batch_6a38417151208190a130bdb18576e17e completed June 21, 2026, 7:54 p.m.
Created at: May 3, 2026, 4:04 p.m.