Triple

T34358291
Position Surface form Disambiguated ID Type / Status
Subject Dragnet (1987 film) E881798 entity
Predicate hasTagline P7688 FINISHED
Object Just the Facts.
"Just the Facts." is the famous catchphrase-style tagline associated with the 1987 comedy film adaptation of Dragnet.
E2092628 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: Just the Facts. | Statement: [Dragnet (1987 film), hasTagline, Just the Facts.]
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: Just the Facts.
Triple: [Dragnet (1987 film), hasTagline, Just the Facts.]
Generated description
"Just the Facts." is the famous catchphrase-style tagline associated with the 1987 comedy film adaptation of Dragnet.

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_69f349bd06008190904c2f86c42749e3 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7182688f88190b0601da3d01f0697 completed May 3, 2026, 9:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3704a3b1408190b6b13942fe2cd8cd completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a370577d8e08190848ce63a9865793d completed June 20, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_6a37061b69fc81908c02244b45d74771 completed June 20, 2026, 9:28 p.m.
Created at: May 1, 2026, 1:58 a.m.