Triple

T4556406
Position Surface form Disambiguated ID Type / Status
Subject 2nd Massachusetts Militia Regiment E120489 entity
Predicate hasMember P10 FINISHED
Object Sarah
Sarah is a member of the 2nd Massachusetts Militia Regiment, a historical military unit associated with the state of Massachusetts.
 E453277 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: Sarah | Statement: [2nd Massachusetts Militia Regiment, hasMember, Sarah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sarah
Context triple: [2nd Massachusetts Militia Regiment, hasMember, Sarah]
  • A. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • B. Sarah
    Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
  • C. Sarah
    Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
  • D. Sarah
    Sarah is the birth name of Margaret Fuller, the 19th-century American journalist, critic, and women's rights advocate associated with the Transcendentalist movement.
  • E. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • 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: Sarah
Triple: [2nd Massachusetts Militia Regiment, hasMember, Sarah]
Generated description
Sarah is a member of the 2nd Massachusetts Militia Regiment, a historical military unit associated with the state of Massachusetts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sarah
Target entity description: Sarah is a member of the 2nd Massachusetts Militia Regiment, a historical military unit associated with the state of Massachusetts.
  • A. Sarah
    Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
  • B. Sarah
    Sarah is the birth name of Margaret Fuller, the 19th-century American journalist, critic, and women's rights advocate associated with the Transcendentalist movement.
  • C. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • D. Sarah
    Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
  • E. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd5814f56c8190a65f61f6148b7e5a completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3a139f08190a0211d5848ccdfad completed March 20, 2026, 11:09 p.m.
NEDg Description generation batch_69bdd45654a48190a2e0e39a15991e80 completed March 20, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_69bdd4a6ec948190a0da6094ecf0e6d7 completed March 20, 2026, 11:13 p.m.
Created at: March 20, 2026, 1:09 p.m.