Triple

T15886825
Position Surface form Disambiguated ID Type / Status
Subject Rabba E385211 entity
Predicate hasAlternativeForm P455 FINISHED
Object "Maharat"
Maharat is a pioneering Orthodox Jewish institution that trains and ordains women as spiritual leaders and clergy.
 E1181174 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: "Maharat" | Statement: [Rabba, hasAlternativeForm, "Maharat"]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: "Maharat"
Context triple: [Rabba, hasAlternativeForm, "Maharat"]
  • A. "Al-Muhalla"
    Al-Muhalla is a monumental work of Islamic jurisprudence by Ibn Hazm, renowned for its detailed legal analysis and strong advocacy of the Zahiri (literalist) school of thought.
  • B. Mawlaik
    Mawlaik is a town in northwestern Myanmar’s Sagaing Region, situated along the Chindwin River and serving as a local administrative and trading center.
  • C. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • D. "Malabry"
    Malabry is a former small rural settlement whose name is preserved in local toponymy and historical records.
  • E. Mihna
    The Mihna was an Islamic inquisition instituted in the 9th century that tested and persecuted scholars over their adherence to the doctrine of the createdness of the Qur’an.
  • 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: "Maharat"
Triple: [Rabba, hasAlternativeForm, "Maharat"]
Generated description
Maharat is a pioneering Orthodox Jewish institution that trains and ordains women as spiritual leaders and clergy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: "Maharat"
Target entity description: Maharat is a pioneering Orthodox Jewish institution that trains and ordains women as spiritual leaders and clergy.
  • A. "Al-Muhalla"
    Al-Muhalla is a monumental work of Islamic jurisprudence by Ibn Hazm, renowned for its detailed legal analysis and strong advocacy of the Zahiri (literalist) school of thought.
  • B. Mawlaik
    Mawlaik is a town in northwestern Myanmar’s Sagaing Region, situated along the Chindwin River and serving as a local administrative and trading center.
  • C. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • D. "Malabry"
    Malabry is a former small rural settlement whose name is preserved in local toponymy and historical records.
  • E. Mihna
    The Mihna was an Islamic inquisition instituted in the 9th century that tested and persecuted scholars over their adherence to the doctrine of the createdness of the Qur’an.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561b6fb48190adcf8277e1895fda completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa95791a48190abc79a6906672098 completed May 9, 2026, 9:38 p.m.
NEDg Description generation batch_69ffaa77b2bc81909edda3a7ec29ba58 completed May 9, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69ffaadbe4ec8190bb69a25cde40b316 completed May 9, 2026, 9:45 p.m.
Created at: April 10, 2026, 4:51 a.m.