Triple

T32932523
Position Surface form Disambiguated ID Type / Status
Subject Franklin W. Dixon E842434 entity
Predicate usedInSeries P53947 FINISHED
Object The Hardy Boys Adventures
The Hardy Boys Adventures is a modern reboot of the classic Hardy Boys mystery series, featuring updated, fast-paced detective stories aimed at contemporary middle-grade readers.
E2039327 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: The Hardy Boys Adventures | Statement: [Franklin W. Dixon, usedInSeries, The Hardy Boys Adventures]
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: The Hardy Boys Adventures
Triple: [Franklin W. Dixon, usedInSeries, The Hardy Boys Adventures]
Generated description
The Hardy Boys Adventures is a modern reboot of the classic Hardy Boys mystery series, featuring updated, fast-paced detective stories aimed at contemporary middle-grade readers.

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_69f34948adfc8190a937f1f622783c0b completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d10602d4819099a5c334047ff1bd completed May 3, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525a499488190a360b369e899c743 completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a3526cd1b0c819087599973a5651710 completed June 19, 2026, 11:23 a.m.
NED2 Entity disambiguation (via description) batch_6a352766ac5c8190a15fb9939e4527e6 completed June 19, 2026, 11:26 a.m.
Created at: May 1, 2026, 1:20 a.m.