Triple

T8379771
Position Surface form Disambiguated ID Type / Status
Subject Dabir-ul-Mulk E197658 entity
Predicate hasComponent P35 FINISHED
Object Dabir
Dabir is a historical Persian title referring to a scribe or secretary, often serving in high administrative or courtly roles.
 E729854 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: Dabir | Statement: [Dabir-ul-Mulk, hasComponent, Dabir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dabir
Context triple: [Dabir-ul-Mulk, hasComponent, Dabir]
  • A. Takhuit
    Takhuit was an ancient Egyptian queen of the 26th Dynasty, best known as the mother of Pharaoh Apries.
  • B. M’Chedallah
    M’Chedallah is a town and commune located in northern Algeria’s Bouira Province.
  • C. Sarei HaMeah
    Sarei HaMeah is a significant Hebrew work by Rabbi Yehuda Leib Maimon that profiles and analyzes one hundred prominent rabbinic figures.
  • D. Akhami
    Akhami is an alternative name for the Achomi language, an Iranian language spoken primarily by communities in southern Iran and the Persian Gulf region.
  • E. Zimran
    Zimran is a lesser-known biblical figure mentioned in the Hebrew Bible as one of Abraham's sons by his wife Keturah.
  • 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: Dabir
Triple: [Dabir-ul-Mulk, hasComponent, Dabir]
Generated description
Dabir is a historical Persian title referring to a scribe or secretary, often serving in high administrative or courtly roles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dabir
Target entity description: Dabir is a historical Persian title referring to a scribe or secretary, often serving in high administrative or courtly roles.
  • A. Takhuit
    Takhuit was an ancient Egyptian queen of the 26th Dynasty, best known as the mother of Pharaoh Apries.
  • B. M’Chedallah
    M’Chedallah is a town and commune located in northern Algeria’s Bouira Province.
  • C. Sarei HaMeah
    Sarei HaMeah is a significant Hebrew work by Rabbi Yehuda Leib Maimon that profiles and analyzes one hundred prominent rabbinic figures.
  • D. Akhami
    Akhami is an alternative name for the Achomi language, an Iranian language spoken primarily by communities in southern Iran and the Persian Gulf region.
  • E. Zimran
    Zimran is a lesser-known biblical figure mentioned in the Hebrew Bible as one of Abraham's sons by his wife Keturah.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c3dc1881908081c6a2829deb5a completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde803ac088190ae185ef444c9c7b9 completed April 2, 2026, 3:52 a.m.
NEDg Description generation batch_69cdebf944008190b7e758ac59257e22 completed April 2, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69cdeccedf4081909cab853ee1ff1b82 completed April 2, 2026, 4:13 a.m.
Created at: March 30, 2026, 6:02 p.m.