Triple

T28208319
Position Surface form Disambiguated ID Type / Status
Subject The Way Ahead E717089 entity
Predicate basedOn P98 FINISHED
Object 1943 training film The New Lot
1943 training film The New Lot is a British World War II army instructional drama that follows a group of new recruits through their early military training.
E1809125 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: 1943 training film The New Lot | Statement: [The Way Ahead, basedOn, 1943 training film The New Lot]
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: 1943 training film The New Lot
Triple: [The Way Ahead, basedOn, 1943 training film The New Lot]
Generated description
1943 training film The New Lot is a British World War II army instructional drama that follows a group of new recruits through their early military training.

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_69efd6b826908190857e6e7dad74ed93 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6430fdf488190b01ad19531e96991 completed May 2, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6bc1c808190adf2143e8d701949 completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15eea5fa5c81909fb1262d53e68298 completed May 26, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_6a15ef172c9c8190a7c8c9053b8604fb completed May 26, 2026, 7:05 p.m.
Created at: April 27, 2026, 10:37 p.m.