Triple

T2647809
Position Surface form Disambiguated ID Type / Status
Subject West Texas E53824 entity
Predicate contains P35 FINISHED
Object Snyder
Snyder is a small city in Scurry County, Texas, known historically for its role in the oil and gas industry and as a regional hub in West Texas.
 E61047 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: Snyder | Statement: [West Texas, contains, Snyder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Snyder
Context triple: [West Texas, contains, Snyder]
  • A. Snyder
    Snyder is a surname most prominently associated with Dan Snyder, the American businessman and former owner of the NFL’s Washington Commanders.
  • B. Nolan
    Nolan is a common Irish surname that has been borne by numerous notable figures across fields such as film, sports, and politics.
  • C. Zack Snyder
    Zack Snyder is an American filmmaker known for his visually stylized, action-driven comic book and superhero adaptations such as 300, Watchmen, and multiple DC Extended Universe films.
  • D. Wick
    Wick is a small coastal town in the far north of Scotland, historically known as a fishing port and regional administrative center.
  • E. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • 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: Snyder
Triple: [West Texas, contains, Snyder]
Generated description
Snyder is a small city in Scurry County, Texas, known historically for its role in the oil and gas industry and as a regional hub in West Texas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Snyder
Target entity description: Snyder is a small city in Scurry County, Texas, known historically for its role in the oil and gas industry and as a regional hub in West Texas.
  • A. Snyder chosen
    Snyder is a surname most prominently associated with Dan Snyder, the American businessman and former owner of the NFL’s Washington Commanders.
  • B. Nolan
    Nolan is a common Irish surname that has been borne by numerous notable figures across fields such as film, sports, and politics.
  • C. Zack Snyder
    Zack Snyder is an American filmmaker known for his visually stylized, action-driven comic book and superhero adaptations such as 300, Watchmen, and multiple DC Extended Universe films.
  • D. Wick
    Wick is a small coastal town in the far north of Scotland, historically known as a fishing port and regional administrative center.
  • E. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd919bf2c81908feb768f3391e985 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98c944548190a8dbe9b81045e97b completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af99fcd7348190b7e99d58ce9c363a completed March 10, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_69af9a5938b48190820f37f2e2280438 completed March 10, 2026, 4:13 a.m.
Created at: March 6, 2026, 9:53 p.m.