Triple

T32193154
Position Surface form Disambiguated ID Type / Status
Subject Tom Reese E822319 entity
Predicate notableWork P4 FINISHED
Object The Fugitive
The Fugitive is a 1960s American television drama series about a doctor wrongfully convicted of his wife's murder who flees custody to find the real killer while being pursued by the law.
E955029 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: The Fugitive | Statement: [Tom Reese, notableWork, The Fugitive]
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: The Fugitive
Triple: [Tom Reese, notableWork, The Fugitive]
Generated description
The Fugitive is a 1960s American television drama series about a doctor wrongfully convicted of his wife's murder who flees custody to find the real killer while being pursued by the law.

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_69f3490819cc81909bae1f8ce99423c5 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb35369c8190992fe7dad36a2a9d completed May 3, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0beab55881908c02b07c3e87af9c completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f1b70704c8190850bfb9c02e2ff25 completed June 14, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_6a2f1bfdaec481909bc83ad0142de144 completed June 14, 2026, 9:24 p.m.
Created at: May 1, 2026, 12:35 a.m.