Triple

T16506706
Position Surface form Disambiguated ID Type / Status
Subject Landsat 9 E400949 entity
Predicate instrument P792 FINISHED
Object OLI-2
OLI-2 is the Operational Land Imager sensor aboard the Landsat 9 satellite, designed to capture multispectral Earth observation imagery for environmental monitoring and land-use analysis.
 E1217266 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: OLI-2 | Statement: [Landsat 9, instrument, OLI-2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OLI-2
Context triple: [Landsat 9, instrument, OLI-2]
  • A. Ollii
    The Ollii were an ancient Roman family (gens) to which Titus Ollius belonged.
  • B. OLIN
    OLIN is a prominent landscape architecture and urban design firm known for shaping major public spaces and environmentally responsive projects worldwide.
  • C. Olib
    Olib is a small Croatian island in the Adriatic Sea, known for its tranquil atmosphere, clear waters, and traditional Mediterranean village life.
  • D. OROLSI
    OROLSI is a United Nations office responsible for supporting rule of law, security sector reform, and related institution-building in conflict and post-conflict settings.
  • E. Oluvil
    Oluvil is a coastal town in Sri Lanka’s Eastern Province, known for its fishing harbor and as a regional center for education and commerce.
  • 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: OLI-2
Triple: [Landsat 9, instrument, OLI-2]
Generated description
OLI-2 is the Operational Land Imager sensor aboard the Landsat 9 satellite, designed to capture multispectral Earth observation imagery for environmental monitoring and land-use analysis.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OLI-2
Target entity description: OLI-2 is the Operational Land Imager sensor aboard the Landsat 9 satellite, designed to capture multispectral Earth observation imagery for environmental monitoring and land-use analysis.
  • A. Ollii
    The Ollii were an ancient Roman family (gens) to which Titus Ollius belonged.
  • B. OLIN
    OLIN is a prominent landscape architecture and urban design firm known for shaping major public spaces and environmentally responsive projects worldwide.
  • C. Olib
    Olib is a small Croatian island in the Adriatic Sea, known for its tranquil atmosphere, clear waters, and traditional Mediterranean village life.
  • D. OROLSI
    OROLSI is a United Nations office responsible for supporting rule of law, security sector reform, and related institution-building in conflict and post-conflict settings.
  • E. Oluvil
    Oluvil is a coastal town in Sri Lanka’s Eastern Province, known for its fishing harbor and as a regional center for education and commerce.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e52a2b48190ae715e7db0fd3aad completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a005832bcb48190a905ee7c9bff2c5b completed May 10, 2026, 10:04 a.m.
NEDg Description generation batch_6a0059126e588190b531c145f3c155b4 completed May 10, 2026, 10:08 a.m.
NED2 Entity disambiguation (via description) batch_6a0059b5a1f8819089caefc121246739 completed May 10, 2026, 10:11 a.m.
Created at: April 10, 2026, 5:14 a.m.