Triple

T299271
Position Surface form Disambiguated ID Type / Status
Subject chicken E6161 entity
Predicate hasCommonBreed P7254 FINISHED
Object Marans
Marans is a French chicken breed renowned for its dark chocolate-brown eggs and dual-purpose use for both meat and egg production.
E39458 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: Marans | Statement: [chicken, hasCommonBreed, Marans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marans
Context triple: [chicken, hasCommonBreed, Marans]
  • A. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • B. Gallic rooster
    The Gallic rooster is a traditional emblem of France, symbolizing the nation’s pride, vigilance, and cultural identity.
  • C. Silkie
    Silkie is a distinctive chicken breed known for its fluffy, silk-like plumage, black skin, and gentle temperament, often kept as an ornamental or pet bird.
  • D. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • E. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • 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: Marans
Triple: [chicken, hasCommonBreed, Marans]
Generated description
Marans is a French chicken breed renowned for its dark chocolate-brown eggs and dual-purpose use for both meat and egg production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marans
Target entity description: Marans is a French chicken breed renowned for its dark chocolate-brown eggs and dual-purpose use for both meat and egg production.
  • A. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • B. Gallic rooster
    The Gallic rooster is a traditional emblem of France, symbolizing the nation’s pride, vigilance, and cultural identity.
  • C. Silkie
    Silkie is a distinctive chicken breed known for its fluffy, silk-like plumage, black skin, and gentle temperament, often kept as an ornamental or pet bird.
  • D. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • E. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ee002dd0819080f0841eb9107ee3 completed Feb. 28, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b47185f48190813159f932c0af9a completed March 1, 2026, 3:37 a.m.
NEDg Description generation batch_69a3b4da227c8190bb172bb78484ce46 completed March 1, 2026, 3:39 a.m.
NED2 Entity disambiguation (via description) batch_69a3b52e995c819084fe2b4983f6cfcc completed March 1, 2026, 3:40 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.