Triple

T14958120
Position Surface form Disambiguated ID Type / Status
Subject Miss Hannigan E372985 entity
Predicate ward P21208 FINISHED
Object Molly
Molly is the youngest and most endearing orphan girl in the musical "Annie," known for her sweetness and vulnerability.
 E1129292 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: Molly | Statement: [Miss Hannigan, ward, Molly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molly
Context triple: [Miss Hannigan, ward, Molly]
  • A. Molly
    Molly is the central female protagonist in the 1926 silent film "Sparrows," portrayed by Mary Pickford.
  • B. Molly
    Molly is a fictional character played by Irish actress Dominique McElligott, known from her work in film and television.
  • C. Molly
    Molly is a feminine given name commonly used in English-speaking countries, often as a diminutive of Mary.
  • D. Molly
    Molly is the adventurous young chicken protagonist of the animated film "Chicken Run: Dawn of the Nugget," who drives the story’s escape mission.
  • E. Molly
    Molly is a character from the 1973 crime film "Charley Varrick," which follows a small-time crook entangled with the mob after a bank heist.
  • 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: Molly
Triple: [Miss Hannigan, ward, Molly]
Generated description
Molly is the youngest and most endearing orphan girl in the musical "Annie," known for her sweetness and vulnerability.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molly
Target entity description: Molly is the youngest and most endearing orphan girl in the musical "Annie," known for her sweetness and vulnerability.
  • A. Molly
    Molly is a fictional character played by Irish actress Dominique McElligott, known from her work in film and television.
  • B. Molly
    Molly is the central female character in James Joyce’s novel "Ulysses," renowned for her candid, stream-of-consciousness monologue that concludes the book.
  • C. Molly
    Molly is a feminine given name commonly used in English-speaking countries, often as a diminutive of Mary.
  • D. Molly
    Molly is a lesser-known sibling of Snoopy in the Peanuts comic universe created by Charles M. Schulz.
  • E. Molly
    Molly is the adventurous young chicken protagonist of the animated film "Chicken Run: Dawn of the Nugget," who drives the story’s escape mission.
  • 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6cd85bc81909040b7ff78f62554 completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e9e74fc8190bdd10a25c39829f3 completed May 9, 2026, 12:23 a.m.
NEDg Description generation batch_69fe83269020819085b904e080578580 completed May 9, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_69fe83ccc73881909c28c53052c4cd86 completed May 9, 2026, 12:46 a.m.
Created at: April 10, 2026, 2:40 a.m.