Triple

T1455886
Position Surface form Disambiguated ID Type / Status
Subject Henry Alsberg E31398 entity
Predicate familyName P18 FINISHED
Object Alsberg
Alsberg is a surname of Germanic origin borne by various notable individuals, including American writer and theater director Henry Alsberg.
 E166571 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: Alsberg | Statement: [Henry Alsberg, familyName, Alsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alsberg
Context triple: [Henry Alsberg, familyName, Alsberg]
  • A. Mount Eisen
    Mount Eisen is a peak in California’s Sierra Nevada range, situated along the rugged Great Western Divide within Sequoia National Park.
  • B. Wilseder Berg
    Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
  • C. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • D. Nadelhorn
    Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing routes.
  • E. Bishorn
    Bishorn is a 4,153-meter-high glaciated mountain in the Swiss Alps, popular with climbers for its relatively accessible ascent and panoramic views.
  • 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: Alsberg
Triple: [Henry Alsberg, familyName, Alsberg]
Generated description
Alsberg is a surname of Germanic origin borne by various notable individuals, including American writer and theater director Henry Alsberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alsberg
Target entity description: Alsberg is a surname of Germanic origin borne by various notable individuals, including American writer and theater director Henry Alsberg.
  • A. Mount Eisen
    Mount Eisen is a peak in California’s Sierra Nevada range, situated along the rugged Great Western Divide within Sequoia National Park.
  • B. Wilseder Berg
    Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
  • C. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • D. Nadelhorn
    Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing routes.
  • E. Bishorn
    Bishorn is a 4,153-meter-high glaciated mountain in the Swiss Alps, popular with climbers for its relatively accessible ascent and panoramic views.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c581714881909bf4c2bad9645176 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e746b64819091079ff26a60a12e completed March 8, 2026, 5:51 a.m.
NEDg Description generation batch_69ad0ef49014819090feb507a6c04eb4 completed March 8, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_69ad0f5240b88190b515f811c849c841 completed March 8, 2026, 5:55 a.m.
Created at: March 1, 2026, 8 p.m.