Triple

T13594732
Position Surface form Disambiguated ID Type / Status
Subject Lt. Mike Stone E324786 entity
Predicate givenName P17 FINISHED
Object Mike
Mike is the given name of Lt. Mike Stone, a fictional San Francisco homicide detective from the television series "The Streets of San Francisco."
 E1048395 NE FINISHED

How this triple was built (4 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: Mike | Statement: [Lt. Mike Stone, givenName, Mike]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mike
Context triple: [Lt. Mike Stone, givenName, Mike]
  • A. Mike
    Mike is a character in Terrence McNally’s play "The Lisbon Traviata," which explores themes of friendship, obsession, and gay relationships.
  • B. Mike
    Mike is the young boy protagonist of the 1992 family adventure film "Radio Flyer," which centers on his imaginative efforts to escape a troubled home life with his brother.
  • C. Mike
    Mike is the central con artist protagonist in David Mamet’s 1987 psychological thriller film "House of Games."
  • D. Mike
    Mike is the nickname of the fictional character Macaulay "Mike" Connor.
  • E. Mike
    Mike is the commonly used nickname for Robert Michael Bellotti.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Mike
Triple: [Lt. Mike Stone, givenName, Mike]
Generated description
Mike is the given name of Lt. Mike Stone, a fictional San Francisco homicide detective from the television series "The Streets of San Francisco."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mike
Target entity description: Mike is the given name of Lt. Mike Stone, a fictional San Francisco homicide detective from the television series "The Streets of San Francisco."
  • A. Mike
    Mike is a character in Terrence McNally’s play "The Lisbon Traviata," which explores themes of friendship, obsession, and gay relationships.
  • B. Mike
    Mike is the young boy protagonist of the 1992 family adventure film "Radio Flyer," which centers on his imaginative efforts to escape a troubled home life with his brother.
  • C. Mike
    Mike is the central con artist protagonist in David Mamet’s 1987 psychological thriller film "House of Games."
  • D. Mike
    Mike is the nickname of the fictional character Macaulay "Mike" Connor.
  • E. Mike
    Mike is the commonly used nickname for Robert Michael Bellotti.
  • F. None of above. chosen

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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc762a08190b5d29cef9923da84 completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77643b0348190962bf23a9857edbe completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f7791add908190af69b23a54eb7560 completed May 3, 2026, 4:34 p.m.
Created at: April 9, 2026, 9:49 p.m.