Triple

T9453671
Position Surface form Disambiguated ID Type / Status
Subject OGLE-III E227959 entity
Predicate successor P78 FINISHED
Object OGLE-IV
OGLE-IV is the fourth phase of the Optical Gravitational Lensing Experiment, a large-scale astronomical survey focused on detecting microlensing events and variable stars using advanced wide-field imaging.
 E800554 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: OGLE-IV | Statement: [OGLE-III, successor, OGLE-IV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OGLE-IV
Context triple: [OGLE-III, successor, OGLE-IV]
  • A. O-4
    O-4 is a major Turkish motorway forming part of the country's primary east–west highway network.
  • B. Avgo
    Avgo is a notable summit of Mount Pangaion in northern Greece, known for its rugged terrain and scenic views.
  • C. Avisio
    Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
  • D. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • E. Gemini 1.5
    Gemini 1.5 is an advanced version of Google’s Gemini AI model family, offering improved multimodal reasoning and performance over earlier releases.
  • 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: OGLE-IV
Triple: [OGLE-III, successor, OGLE-IV]
Generated description
OGLE-IV is the fourth phase of the Optical Gravitational Lensing Experiment, a large-scale astronomical survey focused on detecting microlensing events and variable stars using advanced wide-field imaging.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OGLE-IV
Target entity description: OGLE-IV is the fourth phase of the Optical Gravitational Lensing Experiment, a large-scale astronomical survey focused on detecting microlensing events and variable stars using advanced wide-field imaging.
  • A. O-4
    O-4 is a major Turkish motorway forming part of the country's primary east–west highway network.
  • B. Avgo
    Avgo is a notable summit of Mount Pangaion in northern Greece, known for its rugged terrain and scenic views.
  • C. Avisio
    Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
  • D. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • E. Gemini 1.5
    Gemini 1.5 is an advanced version of Google’s Gemini AI model family, offering improved multimodal reasoning and performance over earlier releases.
  • 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f8c7b3481909c1182b41d8c27a9 completed April 1, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1227b4fc881908c03409f78de1a87 completed April 4, 2026, 2:38 p.m.
NEDg Description generation batch_69d1233a63d481908e322b7e86b5d124 completed April 4, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69d123d32c808190985da2639d2120f7 completed April 4, 2026, 2:44 p.m.
Created at: March 30, 2026, 7:52 p.m.