Triple
T12271351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SOHO |
E292476
|
entity |
| Predicate | hasInstrument |
P35
|
FINISHED |
| Object |
COSTEP
COSTEP is a scientific instrument aboard the SOHO spacecraft designed to study energetic particles from the Sun and in interplanetary space.
|
E975807
|
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: COSTEP | Statement: [SOHO, hasInstrument, COSTEP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: COSTEP Context triple: [SOHO, hasInstrument, COSTEP]
-
A.
CoST
CoST is the College of Science and Technology at North Carolina A&T State University, offering undergraduate and graduate programs in scientific and technological disciplines.
-
B.
COSTAR
COSTAR was a corrective optics instrument installed on the Hubble Space Telescope to compensate for its primary mirror flaw and restore sharp imaging performance.
-
C.
COST
COST is the stock ticker symbol for Costco Wholesale Corporation, a major American membership-based warehouse retail chain.
-
D.
Stepnica
Stepnica is a small town in northwestern Poland situated on the Szczecin Lagoon, known for its port, fishing traditions, and access to natural coastal landscapes.
-
E.
OpenSTEF
OpenSTEF is an open-source project focused on short-term forecasting of electricity demand and generation to support grid reliability and flexibility.
- 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: COSTEP Triple: [SOHO, hasInstrument, COSTEP]
Generated description
COSTEP is a scientific instrument aboard the SOHO spacecraft designed to study energetic particles from the Sun and in interplanetary space.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: COSTEP Target entity description: COSTEP is a scientific instrument aboard the SOHO spacecraft designed to study energetic particles from the Sun and in interplanetary space.
-
A.
CoST
CoST is the College of Science and Technology at North Carolina A&T State University, offering undergraduate and graduate programs in scientific and technological disciplines.
-
B.
COSTAR
COSTAR was a corrective optics instrument installed on the Hubble Space Telescope to compensate for its primary mirror flaw and restore sharp imaging performance.
-
C.
COST
COST is the stock ticker symbol for Costco Wholesale Corporation, a major American membership-based warehouse retail chain.
-
D.
Stepnica
Stepnica is a small town in northwestern Poland situated on the Szczecin Lagoon, known for its port, fishing traditions, and access to natural coastal landscapes.
-
E.
OpenSTEF
OpenSTEF is an open-source project focused on short-term forecasting of electricity demand and generation to support grid reliability and flexibility.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cee7158819093fff74db6867896 |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e6981b48190a0fc5a571c425be1 |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f622de74f0819096c5f5bf6f938fe7 |
completed | May 2, 2026, 4:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62379746c8190bc9da48775b86dfa |
completed | May 2, 2026, 4:16 p.m. |
Created at: April 8, 2026, 9:52 p.m.