Triple

T13719992
Position Surface form Disambiguated ID Type / Status
Subject Teterboro station E329003 entity
Predicate code P1537 FINISHED
Object TET
TET is the station code for Teterboro station, a rail stop serving the Teterboro area in New Jersey.
 E1056947 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: TET | Statement: [Teterboro station, code, TET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TET
Context triple: [Teterboro station, code, TET]
  • A. TET
    TET is a Ukrainian television channel known for broadcasting entertainment, comedy, and family-oriented programming.
  • B. Tet
    Tet is a river in the Pyrénées-Orientales department of southern France that flows from the Pyrenees to the Mediterranean Sea.
  • C. Tet holiday
    Tet holiday is the Vietnamese Lunar New Year, the country’s most important and widely celebrated festival marking the arrival of spring and a time for family reunions and ancestral worship.
  • D. Tetema
    "Tetema" is a popular Tanzanian Bongo Flava and Afro-pop hit song by Rayvanny, known for its catchy rhythm and widespread success across East Africa and beyond.
  • E. Tetro
    Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
  • 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: TET
Triple: [Teterboro station, code, TET]
Generated description
TET is the station code for Teterboro station, a rail stop serving the Teterboro area in New Jersey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TET
Target entity description: TET is the station code for Teterboro station, a rail stop serving the Teterboro area in New Jersey.
  • A. TET
    TET is a Ukrainian television channel known for broadcasting entertainment, comedy, and family-oriented programming.
  • B. Tet
    Tet is a river in the Pyrénées-Orientales department of southern France that flows from the Pyrenees to the Mediterranean Sea.
  • C. Tet holiday
    Tet holiday is the Vietnamese Lunar New Year, the country’s most important and widely celebrated festival marking the arrival of spring and a time for family reunions and ancestral worship.
  • D. Tetema
    "Tetema" is a popular Tanzanian Bongo Flava and Afro-pop hit song by Rayvanny, known for its catchy rhythm and widespread success across East Africa and beyond.
  • E. Tetro
    Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd439a121c81908cae964e7756274c completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d5c4f848190993f829824eabbef completed May 3, 2026, 7:09 p.m.
NEDg Description generation batch_69f79e77b5e88190a85f4061c8abb8a4 completed May 3, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69f79fa5249481909b2c046ed9801371 completed May 3, 2026, 7:19 p.m.
Created at: April 9, 2026, 9:55 p.m.