Triple

T7130124
Position Surface form Disambiguated ID Type / Status
Subject Peter Scolari E166164 entity
Predicate televisionSeries P3279 FINISHED
Object Dweebs
Dweebs is a short-lived 1990s American sitcom about a group of socially awkward computer geeks working at a tech company.
 E643283 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: Dweebs | Statement: [Peter Scolari, televisionSeries, Dweebs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dweebs
Context triple: [Peter Scolari, televisionSeries, Dweebs]
  • A. Frikes
    Frikes is a small coastal village and fishing harbor on the Greek island of Ithaca, known for its traditional tavernas and scenic bay.
  • B. Denguin
    Denguin is a small commune in southwestern France, located in the Pyrénées-Atlantiques department in the Nouvelle-Aquitaine region.
  • C. Cooties
    Cooties is a 2014 horror-comedy film about elementary school teachers fighting off a playground zombie outbreak caused by tainted chicken nuggets.
  • D. Doozer
    Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
  • E. Tukkies
    Tukkies is the popular nickname for the University of Pretoria, a major public research university in South Africa.
  • 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: Dweebs
Triple: [Peter Scolari, televisionSeries, Dweebs]
Generated description
Dweebs is a short-lived 1990s American sitcom about a group of socially awkward computer geeks working at a tech company.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dweebs
Target entity description: Dweebs is a short-lived 1990s American sitcom about a group of socially awkward computer geeks working at a tech company.
  • A. Frikes
    Frikes is a small coastal village and fishing harbor on the Greek island of Ithaca, known for its traditional tavernas and scenic bay.
  • B. Denguin
    Denguin is a small commune in southwestern France, located in the Pyrénées-Atlantiques department in the Nouvelle-Aquitaine region.
  • C. Cooties
    Cooties is a 2014 horror-comedy film about elementary school teachers fighting off a playground zombie outbreak caused by tainted chicken nuggets.
  • D. Doozer
    Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
  • E. Tukkies
    Tukkies is the popular nickname for the University of Pretoria, a major public research university in South Africa.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e66dc2388190bdec018f1cc6b20a completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a33eea0481909f87e0813bc35b52 completed March 28, 2026, 9:45 a.m.
NEDg Description generation batch_69c7a3f2b51c81909f058149e9bd9f0a completed March 28, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_69c7a4a9e91881909df07f1c540f191e completed March 28, 2026, 9:51 a.m.
Created at: March 27, 2026, 2:44 p.m.