Triple

T29920420
Position Surface form Disambiguated ID Type / Status
Subject Frank Towns E759911 entity
Predicate conflictsWith P4897 FINISHED
Object Heinrich Dorfmann
Heinrich Dorfmann is a brilliant but arrogant German engineer in the 1965 film "The Flight of the Phoenix," whose unorthodox ideas and clashes with pilot Frank Towns drive the story’s central tension.
E2294099 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: Heinrich Dorfmann | Statement: [Frank Towns, conflictsWith, Heinrich Dorfmann]
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: Heinrich Dorfmann
Triple: [Frank Towns, conflictsWith, Heinrich Dorfmann]
Generated description
Heinrich Dorfmann is a brilliant but arrogant German engineer in the 1965 film "The Flight of the Phoenix," whose unorthodox ideas and clashes with pilot Frank Towns drive the story’s central tension.

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_69f2246189fc8190996b63ee1f9a2374 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67793b72c8190ae654ae110b82d84 completed May 2, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7b7a890aa48190868c3f8e99b9243c completed Aug. 11, 2026, 7:39 p.m.
NEDg Description generation batch_6a7b7ae94da4819089f0fc66dabed666 completed Aug. 11, 2026, 7:41 p.m.
NED2 Entity disambiguation (via description) batch_6a7b7bbb17848190b9d674968c543361 completed Aug. 11, 2026, 7:44 p.m.
Created at: April 29, 2026, 6:14 p.m.