Triple

T8251105
Position Surface form Disambiguated ID Type / Status
Subject Mar Awa III E192957 entity
Predicate title P38 FINISHED
Object Mar
Mar is an honorific ecclesiastical title used for bishops and saints in several Eastern Christian traditions, particularly within Syriac Christianity.
 E721517 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: Mar | Statement: [Mar Awa III, title, Mar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mar
Context triple: [Mar Awa III, title, Mar]
  • A. MA
    MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
  • B. MA
    MA is the vehicle registration code used on license plates for the German city of Mannheim.
  • C. MA
    MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
  • D. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • E. Ma
    Ma is a 2019 psychological horror film starring Octavia Spencer as a lonely woman who befriends a group of teenagers with increasingly disturbing consequences.
  • 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: Mar
Triple: [Mar Awa III, title, Mar]
Generated description
Mar is an honorific ecclesiastical title used for bishops and saints in several Eastern Christian traditions, particularly within Syriac Christianity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mar
Target entity description: Mar is an honorific ecclesiastical title used for bishops and saints in several Eastern Christian traditions, particularly within Syriac Christianity.
  • A. MA
    MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
  • B. MA
    MA is the vehicle registration code used on license plates for the German city of Mannheim.
  • C. MA
    MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
  • D. Ma
    Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
  • E. Ma
    Ma is a 2019 psychological horror film starring Octavia Spencer as a lonely woman who befriends a group of teenagers with increasingly disturbing consequences.
  • 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78c935408190b9196a849a8d3a3e completed March 31, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd3540a0988190b8e48988279403db completed April 1, 2026, 3:09 p.m.
NEDg Description generation batch_69cd37a71af481909e82aa29ae558c4a completed April 1, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_69cd4ef034ec8190a4229b21e6088c79 completed April 1, 2026, 4:59 p.m.
Created at: March 30, 2026, 5:48 p.m.