Triple

T34859618
Position Surface form Disambiguated ID Type / Status
Subject Udonis Haslem E1004828 entity
Predicate nickname P55 FINISHED
Object UD
UD is the nickname of Udonis Haslem, a longtime Miami Heat power forward known for his leadership, toughness, and role in multiple NBA championships.
E2115653 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: UD | Statement: [Udonis Haslem, nickname, UD]
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: UD
Triple: [Udonis Haslem, nickname, UD]
Generated description
UD is the nickname of Udonis Haslem, a longtime Miami Heat power forward known for his leadership, toughness, and role in multiple NBA championships.

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_69f76dbb678081909a247b9b5e1a73ac completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7816425d08190990f80b96b01bc66 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37795ca3408190a89af6b177cba73f completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377ab8b5308190982af72170eef223 completed June 21, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_6a377b68e81c8190945fc86d705cb151 completed June 21, 2026, 5:49 a.m.
Created at: May 3, 2026, 4 p.m.