Triple

T28274528
Position Surface form Disambiguated ID Type / Status
Subject Above Suspicion E712951 entity
Predicate productionCompany P490 FINISHED
Object La Plante Productions
La Plante Productions is a British television production company founded by crime writer and producer Lynda La Plante, known for creating and producing crime dramas and police procedurals.
E1812236 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: La Plante Productions | Statement: [Above Suspicion, productionCompany, La Plante Productions]
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: La Plante Productions
Triple: [Above Suspicion, productionCompany, La Plante Productions]
Generated description
La Plante Productions is a British television production company founded by crime writer and producer Lynda La Plante, known for creating and producing crime dramas and police procedurals.

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_69efb52275788190ae5181ccebef18ce completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6444a545c8190808a36813a6347b0 completed May 2, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1607203894819099bd7f27f3344def completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a161361ba748190b59b1155e7f27b98 completed May 26, 2026, 9:40 p.m.
NED2 Entity disambiguation (via description) batch_6a1614891498819096109f9a10904797 completed May 26, 2026, 9:45 p.m.
Created at: April 27, 2026, 11:19 p.m.