Triple

T34753728
Position Surface form Disambiguated ID Type / Status
Subject 2016–17 OHL season E1001856 entity
Predicate hasAllRookieTeam P194873 FINISHED
Object OHL Second All-Rookie Team
The OHL Second All-Rookie Team is an annual Ontario Hockey League honor recognizing standout first-year players who rank just below the top rookie selections at their positions.
E2119400 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: OHL Second All-Rookie Team | Statement: [2016–17 OHL season, hasAllRookieTeam, OHL Second All-Rookie Team]
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: OHL Second All-Rookie Team
Triple: [2016–17 OHL season, hasAllRookieTeam, OHL Second All-Rookie Team]
Generated description
The OHL Second All-Rookie Team is an annual Ontario Hockey League honor recognizing standout first-year players who rank just below the top rookie selections at their positions.

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_69f76db0fb30819096709d43f9a1f45f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69fd8d8b30d081908ebd1ed79a4af412 completed May 8, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37a89cb9b881909708b536ee827bae completed June 21, 2026, 9:02 a.m.
NEDg Description generation batch_6a37a9cd9850819094e07e59e8dedc96 completed June 21, 2026, 9:07 a.m.
NED2 Entity disambiguation (via description) batch_6a37abd05f4c819089833309fc436419 completed June 21, 2026, 9:16 a.m.
Created at: May 3, 2026, 3:59 p.m.