Triple

T31151046
Position Surface form Disambiguated ID Type / Status
Subject Adyeville, Indiana E794070 entity
Predicate namedAfter P63 FINISHED
Object Andrew J. Adye
Andrew J. Adye was a notable figure significant enough in local history that the community of Adyeville, Indiana, was named in his honor.
 E1982053 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: Andrew J. Adye | Statement: [Adyeville, Indiana, namedAfter, Andrew J. Adye]
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: Andrew J. Adye
Triple: [Adyeville, Indiana, namedAfter, Andrew J. Adye]
Generated description
Andrew J. Adye was a notable figure significant enough in local history that the community of Adyeville, Indiana, was named in his honor.

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_69f224d41bb48190a5621cd1485e3a30 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697efc9b88190b4b47643fc957d1d completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7fb939a08190bc7bb4850999cd27 completed June 14, 2026, 10:17 a.m.
NEDg Description generation batch_6a2e80a633308190a46794c5d992993c completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e817feee48190a55b72e9901e1ba6 completed June 14, 2026, 10:25 a.m.
Created at: April 29, 2026, 9:06 p.m.