Triple

T32873812
Position Surface form Disambiguated ID Type / Status
Subject Pen Tennyson E840865 entity
Predicate notableWork P4 FINISHED
Object There Ain't No Justice
"There Ain't No Justice" is a 1939 British boxing drama film directed by Pen Tennyson, noted for its realistic portrayal of working-class life and the sport's darker side.
 E2026741 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: There Ain't No Justice | Statement: [Pen Tennyson, notableWork, There Ain't No Justice]
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: There Ain't No Justice
Triple: [Pen Tennyson, notableWork, There Ain't No Justice]
Generated description
"There Ain't No Justice" is a 1939 British boxing drama film directed by Pen Tennyson, noted for its realistic portrayal of working-class life and the sport's darker side.

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_69f349436ee88190b72ee12d0f3f508e completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cfea53a08190a0e9de4d07330eb8 completed May 3, 2026, 4:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bd1909ac81908dfc7c4c217fa6b4 completed June 19, 2026, 3:52 a.m.
NEDg Description generation batch_6a34bdc35a24819088892cb8a675a225 completed June 19, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_6a34be6eb1808190a6bc47b8d79489ed completed June 19, 2026, 3:58 a.m.
Created at: May 1, 2026, 1:18 a.m.