Triple

T30037773
Position Surface form Disambiguated ID Type / Status
Subject Tarzan and the Jungle Boy E763208 entity
Predicate follows P134 FINISHED
Object Tarzan and the Great River
Tarzan and the Great River is a 1967 adventure film in the Tarzan series, featuring the jungle hero battling river-based threats and villains in the Amazon.
 E1900221 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: Tarzan and the Great River | Statement: [Tarzan and the Jungle Boy, follows, Tarzan and the Great River]
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: Tarzan and the Great River
Triple: [Tarzan and the Jungle Boy, follows, Tarzan and the Great River]
Generated description
Tarzan and the Great River is a 1967 adventure film in the Tarzan series, featuring the jungle hero battling river-based threats and villains in the Amazon.

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_69f2246fb2b88190acff36bf7975c8f0 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f679d581fc819090781408630f6e27 completed May 2, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2743108c808190aef024a7a1e8f439 completed June 8, 2026, 10:32 p.m.
NEDg Description generation batch_6a2746d530488190aeb0698b7f3e7243 completed June 8, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a274768213081908303cca56e0ac2dd completed June 8, 2026, 10:51 p.m.
Created at: April 29, 2026, 6:51 p.m.