Triple

T30524844
Position Surface form Disambiguated ID Type / Status
Subject Richard Wenk E776804 entity
Predicate directed P7373 FINISHED
Object Just the Ticket
Just the Ticket is a 1998 romantic comedy film starring Andy García and Andie MacDowell about a luckless New York ticket scalper trying to turn his life around.
 E1918563 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 Ticket | Statement: [Richard Wenk, directed, Just the Ticket]
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 Ticket
Triple: [Richard Wenk, directed, Just the Ticket]
Generated description
Just the Ticket is a 1998 romantic comedy film starring Andy García and Andie MacDowell about a luckless New York ticket scalper trying to turn his life around.

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_69f2249b23c4819087fa85496d92f43f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6880d55688190b742c534bc7d62d9 completed May 2, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be767fe88190b72b41c88cb22aab completed June 9, 2026, 7:19 a.m.
NEDg Description generation batch_6a27c3264ab48190b0e913e2e7001f8a completed June 9, 2026, 7:39 a.m.
NED2 Entity disambiguation (via description) batch_6a27c3c9d4b88190afdfbba3bc0d081a completed June 9, 2026, 7:42 a.m.
Created at: April 29, 2026, 8:17 p.m.