Triple
T4065650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GOSAT |
E86316
|
entity |
| Predicate | instrument |
P792
|
FINISHED |
| Object |
TANSO-FTS
TANSO-FTS is a high-resolution Fourier transform spectrometer aboard Japan’s GOSAT satellite used to measure greenhouse gases like carbon dioxide and methane in Earth’s atmosphere.
|
E410454
|
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: TANSO-FTS | Statement: [GOSAT, instrument, TANSO-FTS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TANSO-FTS Context triple: [GOSAT, instrument, TANSO-FTS]
-
A.
TSO
TSO (The Stationery Office) is a major UK publishing and information services company known for producing and distributing official government and public sector documents.
-
B.
tso
tso is the ISO 639-2 three-letter code for the Tsonga language, a Bantu language spoken primarily in southern Africa.
-
C.
FTU
FTU is a leading Vietnamese university renowned for its programs in economics, business, and international trade.
-
D.
T-Engineering
T-Engineering is an engineering firm known for its role in designing major infrastructure projects, including the Yavuz Sultan Selim Bridge in Turkey.
-
E.
Futrono
Futrono is a lakeside town and commune in southern Chile known for its scenic setting on Lake Ranco and its role in the Los Ríos Region’s tourism and agriculture.
- 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: TANSO-FTS Triple: [GOSAT, instrument, TANSO-FTS]
Generated description
TANSO-FTS is a high-resolution Fourier transform spectrometer aboard Japan’s GOSAT satellite used to measure greenhouse gases like carbon dioxide and methane in Earth’s atmosphere.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TANSO-FTS Target entity description: TANSO-FTS is a high-resolution Fourier transform spectrometer aboard Japan’s GOSAT satellite used to measure greenhouse gases like carbon dioxide and methane in Earth’s atmosphere.
-
A.
TSO
TSO (The Stationery Office) is a major UK publishing and information services company known for producing and distributing official government and public sector documents.
-
B.
tso
tso is the ISO 639-2 three-letter code for the Tsonga language, a Bantu language spoken primarily in southern Africa.
-
C.
FTU
FTU is a leading Vietnamese university renowned for its programs in economics, business, and international trade.
-
D.
T-Engineering
T-Engineering is an engineering firm known for its role in designing major infrastructure projects, including the Yavuz Sultan Selim Bridge in Turkey.
-
E.
Futrono
Futrono is a lakeside town and commune in southern Chile known for its scenic setting on Lake Ranco and its role in the Los Ríos Region’s tourism and agriculture.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf58d9c8190936e453b0d397cb0 |
completed | March 9, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562b17c888190ac4771f2bb4f0d58 |
completed | March 14, 2026, 1:29 p.m. |
| NEDg | Description generation | batch_69b5637e72948190989169b0a46916a8 |
completed | March 14, 2026, 1:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b563fc4cb081908ba0f1a799338a8c |
completed | March 14, 2026, 1:34 p.m. |
Created at: March 9, 2026, 3:38 p.m.