Triple

T29675957
Position Surface form Disambiguated ID Type / Status
Subject Party Clown E750814 entity
Predicate associatedWork P922 FINISHED
Object On the Line
On the Line is a 2001 romantic comedy film starring Lance Bass and Joey Fatone about a shy young man’s quest to find a woman he met on a Chicago train.
 E600862 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: On the Line | Statement: [Party Clown, associatedWork, On the Line]
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: On the Line
Triple: [Party Clown, associatedWork, On the Line]
Generated description
On the Line is a 2001 romantic comedy film starring Lance Bass and Joey Fatone about a shy young man’s quest to find a woman he met on a Chicago train.

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_69f0d624d7b08190ba237d226f78d0d9 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f6725dadb081909ef2fbba8d3fd935 completed May 2, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1abec6c8190b8ff6fe5eda2e390 completed June 8, 2026, 4:45 p.m.
NEDg Description generation batch_6a26f5850b44819097a4d2fbbf1a27aa completed June 8, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_6a26f8484c6c819095f2718c50d70bdd completed June 8, 2026, 5:13 p.m.
Created at: April 28, 2026, 7:07 p.m.