Triple

T10861819
Position Surface form Disambiguated ID Type / Status
Subject Ammergau Alps E256423 entity
Predicate hasPeak P8205 FINISHED
Object Laber
Laber is a mountain peak in the Ammergau Alps of Bavaria, Germany, known for its panoramic views and accessibility via a cable car.
E891294 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: Laber | Statement: [Ammergau Alps, hasPeak, Laber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laber
Context triple: [Ammergau Alps, hasPeak, Laber]
  • A. Laber
    Laber is a river in Bavaria, Germany, that flows through the Regensburg district.
  • B. Labori
    Labori was a prominent French defense lawyer best known for representing Alfred Dreyfus during the politically charged Dreyfus affair.
  • C. Labo
    Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
  • D. Laborec
    Laborec is a river in eastern Slovakia that flows through the Carpathian region and is a tributary of the Latorica River.
  • E. The Grinder
    The Grinder is an American television sitcom that satirizes legal dramas, starring Rob Lowe and Fred Savage as brothers whose lives are upended when a TV lawyer returns home believing he can practice real law.
  • 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: Laber
Triple: [Ammergau Alps, hasPeak, Laber]
Generated description
Laber is a mountain peak in the Ammergau Alps of Bavaria, Germany, known for its panoramic views and accessibility via a cable car.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Laber
Target entity description: Laber is a mountain peak in the Ammergau Alps of Bavaria, Germany, known for its panoramic views and accessibility via a cable car.
  • A. Laber
    Laber is a river in Bavaria, Germany, that flows through the Regensburg district.
  • B. Labori
    Labori was a prominent French defense lawyer best known for representing Alfred Dreyfus during the politically charged Dreyfus affair.
  • C. Labo
    Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
  • D. Laborec
    Laborec is a river in eastern Slovakia that flows through the Carpathian region and is a tributary of the Latorica River.
  • E. The Grinder
    The Grinder is an American television sitcom that satirizes legal dramas, starring Rob Lowe and Fred Savage as brothers whose lives are upended when a TV lawyer returns home believing he can practice real law.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7515186f08190a5cc388a7d936c4f completed April 9, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7d350748190821a4413c1eb7106 completed April 15, 2026, 8:40 p.m.
NEDg Description generation batch_69e0b498df2481908c964d53b1782774 completed April 16, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_69e11e21fc2c8190878a877ecd3b465e completed April 16, 2026, 5:36 p.m.
Created at: April 8, 2026, 9:20 p.m.