Triple

T21553776
Position Surface form Disambiguated ID Type / Status
Subject Gil Santos E531831 entity
Predicate employer P7 FINISHED
Object WITS (Boston radio station)
WITS was a Boston-area AM radio station best known as a sports broadcaster, including serving as a flagship station for local professional teams.
 E58903 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: WITS (Boston radio station) | Statement: [Gil Santos, employer, WITS (Boston radio station)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WITS (Boston radio station)
Context triple: [Gil Santos, employer, WITS (Boston radio station)]
  • A. WIII
    WIII is the ICAO airport code for Soekarno–Hatta International Airport, the main international gateway serving Jakarta, Indonesia.
  • B. WLIB
    WLIB is a New York City AM radio station known for its urban contemporary gospel and talk programming, serving primarily African American and Caribbean audiences.
  • C. WBZ-FM
    WBZ-FM is a Boston-area sports radio station known for its all-sports format and coverage of local professional teams.
  • D. WOR (AM)
    WOR (AM) is a long-running New York City talk radio station known for its news, talk, and syndicated programming.
  • E. WINS (AM)
    WINS (AM) is a New York City all-news radio station known for its 24-hour news format and the slogan "You give us 22 minutes, we'll give you the world."
  • 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: WITS (Boston radio station)
Triple: [Gil Santos, employer, WITS (Boston radio station)]
Generated description
WITS was a Boston-area AM radio station best known as a sports broadcaster, including serving as a flagship station for local professional teams.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WITS (Boston radio station)
Target entity description: WITS was a Boston-area AM radio station best known as a sports broadcaster, including serving as a flagship station for local professional teams.
  • A. WIII
    WIII is the ICAO airport code for Soekarno–Hatta International Airport, the main international gateway serving Jakarta, Indonesia.
  • B. WLIB
    WLIB is a New York City AM radio station known for its urban contemporary gospel and talk programming, serving primarily African American and Caribbean audiences.
  • C. WBZ-FM chosen
    WBZ-FM is a Boston-area sports radio station known for its all-sports format and coverage of local professional teams.
  • D. WOR (AM)
    WOR (AM) is a long-running New York City talk radio station known for its news, talk, and syndicated programming.
  • E. WINS (AM)
    WINS (AM) is a New York City all-news radio station known for its 24-hour news format and the slogan "You give us 22 minutes, we'll give you the world."
  • F. None of above.

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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb594956c8190a5b4d81911e3927d completed April 27, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09eee58b088190a5cfcbbe7b095bc6 completed May 17, 2026, 4:37 p.m.
NEDg Description generation batch_6a09f033a55c81908d221e4b5c9c1b95 completed May 17, 2026, 4:43 p.m.
NED2 Entity disambiguation (via description) batch_6a09f0cb21a081908afa371741754eaa completed May 17, 2026, 4:46 p.m.
Created at: April 16, 2026, 6:29 p.m.