Triple

T3285693
Position Surface form Disambiguated ID Type / Status
Subject B.P.R.D. E68975 entity
Predicate employs P7 FINISHED
Object Panya
Panya is a character in the Hellboy/B.P.R.D. comic universe, an ancient Egyptian woman with psychic abilities who becomes a key supernatural asset to the Bureau for Paranormal Research and Defense.
 E344082 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: Panya | Statement: [B.P.R.D., employs, Panya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Panya
Context triple: [B.P.R.D., employs, Panya]
  • A. Banna
    Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
  • B. Nambya
    Nambya are a Bantu-speaking ethnic group primarily found in northwestern Zimbabwe and parts of Botswana, known for their distinct language and cultural traditions.
  • C. Pinara
    Pinara was an important ancient Lycian city in southwestern Anatolia, known for its rock-cut tombs and well-preserved ruins.
  • D. Sharya
    Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
  • E. Alinda
    Alinda was an important ancient city in the region of Caria in southwestern Anatolia, known for its strategic location and well-preserved Hellenistic ruins.
  • 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: Panya
Triple: [B.P.R.D., employs, Panya]
Generated description
Panya is a character in the Hellboy/B.P.R.D. comic universe, an ancient Egyptian woman with psychic abilities who becomes a key supernatural asset to the Bureau for Paranormal Research and Defense.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Panya
Target entity description: Panya is a character in the Hellboy/B.P.R.D. comic universe, an ancient Egyptian woman with psychic abilities who becomes a key supernatural asset to the Bureau for Paranormal Research and Defense.
  • A. Banna
    Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
  • B. Nambya
    Nambya are a Bantu-speaking ethnic group primarily found in northwestern Zimbabwe and parts of Botswana, known for their distinct language and cultural traditions.
  • C. Pinara
    Pinara was an important ancient Lycian city in southwestern Anatolia, known for its rock-cut tombs and well-preserved ruins.
  • D. Sharya
    Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
  • E. Alinda
    Alinda was an important ancient city in the region of Caria in southwestern Anatolia, known for its strategic location and well-preserved Hellenistic ruins.
  • 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_69ad859c463481909ca4be267336c290 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb03918c48190987d7cfd3bda9716 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e85b6a1081908581b2040b8ce261 completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e9783918819085ea73a8ed815f65 completed March 12, 2026, 4:27 p.m.
NED2 Entity disambiguation (via description) batch_69b2ea0189948190b1dab60aecf04b73 completed March 12, 2026, 4:29 p.m.
Created at: March 8, 2026, 3:10 p.m.