Triple

T34708346
Position Surface form Disambiguated ID Type / Status
Subject American Cancer Society Medal of Honor E1000567 entity
Predicate alsoKnownAs P39 FINISHED
Object ACS Medal of Honor
The ACS Medal of Honor is the American Cancer Society’s highest award, presented to individuals who have made outstanding contributions to the fight against cancer through research, clinical care, or public service.
E2108155 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: ACS Medal of Honor | Statement: [American Cancer Society Medal of Honor, alsoKnownAs, ACS Medal of Honor]
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: ACS Medal of Honor
Triple: [American Cancer Society Medal of Honor, alsoKnownAs, ACS Medal of Honor]
Generated description
The ACS Medal of Honor is the American Cancer Society’s highest award, presented to individuals who have made outstanding contributions to the fight against cancer through research, clinical care, or public service.

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_69f76dab937881909c86f1b9ad50445f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779766fcc8190a4d486d9a239b979 completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37530bb92c81908ace2b43c240a312 completed June 21, 2026, 2:57 a.m.
NEDg Description generation batch_6a37538a0d948190949592c8f833958c completed June 21, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_6a37541fa8d48190aef474f094893f32 completed June 21, 2026, 3:01 a.m.
Created at: May 3, 2026, 3:59 p.m.