Triple

T5012807
Position Surface form Disambiguated ID Type / Status
Subject Werra E112665 entity
Predicate hasLeftTributary P415 FINISHED
Object Felda
Felda is a small river in central Germany that flows through Hesse and Thuringia before joining the Werra.
 E486413 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: Felda | Statement: [Werra, hasLeftTributary, Felda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Felda
Context triple: [Werra, hasLeftTributary, Felda]
  • A. Brown Field
    Brown Field is a military training area associated with the United States Marine Corps Officer Candidates School.
  • B. Bunge Land
    Bunge Land is a low-lying, largely sandy Arctic island or landmass within Russia’s New Siberian Islands archipelago, known for being periodically flooded by the sea.
  • C. The Great Field
    The Great Field is an ancient Egyptian royal burial ground on the west bank of the Nile at Luxor, renowned for its rock-cut tombs of New Kingdom pharaohs and nobles.
  • D. Palmland
    Palmland was a named passenger train operated by the Seaboard Air Line Railroad that provided long-distance service in the southeastern United States.
  • E. Paprika Plains
    "Paprika Plains" is an expansive, jazz-influenced, multi-section piano suite by Joni Mitchell, noted for its atmospheric storytelling and experimental structure.
  • 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: Felda
Triple: [Werra, hasLeftTributary, Felda]
Generated description
Felda is a small river in central Germany that flows through Hesse and Thuringia before joining the Werra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Felda
Target entity description: Felda is a small river in central Germany that flows through Hesse and Thuringia before joining the Werra.
  • A. Brown Field
    Brown Field is a military training area associated with the United States Marine Corps Officer Candidates School.
  • B. Bunge Land
    Bunge Land is a low-lying, largely sandy Arctic island or landmass within Russia’s New Siberian Islands archipelago, known for being periodically flooded by the sea.
  • C. The Great Field
    The Great Field is an ancient Egyptian royal burial ground on the west bank of the Nile at Luxor, renowned for its rock-cut tombs of New Kingdom pharaohs and nobles.
  • D. Palmland
    Palmland was a named passenger train operated by the Seaboard Air Line Railroad that provided long-distance service in the southeastern United States.
  • E. Paprika Plains
    "Paprika Plains" is an expansive, jazz-influenced, multi-section piano suite by Joni Mitchell, noted for its atmospheric storytelling and experimental structure.
  • 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_69bd4434acb8819086679dbeccc2fe54 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd730f12a481908a27c15dc73987c6 completed March 20, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69be926e5ef481909df3a4b9d793300a completed March 21, 2026, 12:43 p.m.
NEDg Description generation batch_69be93efbf548190b2967a41162f2e4e completed March 21, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_69be945978a48190821103cdd306075d completed March 21, 2026, 12:51 p.m.
Created at: March 20, 2026, 1:35 p.m.