Triple
T4065651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GOSAT |
E86316
|
entity |
| Predicate | instrument |
P792
|
FINISHED |
| Object |
TANSO-CAI
TANSO-CAI is a satellite-borne imaging instrument on Japan’s GOSAT mission designed to monitor clouds and aerosols to support greenhouse gas observations.
|
E410455
|
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-CAI | Statement: [GOSAT, instrument, TANSO-CAI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TANSO-CAI Context triple: [GOSAT, instrument, TANSO-CAI]
-
A.
Tunechi
Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
-
B.
TOICA
TOICA is a rechargeable contactless smart card used for fare payment on trains and buses in the Nagoya area and other parts of Japan’s JR Central network.
-
C.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
-
D.
Kannon
Kannon is the Japanese name for the bodhisattva of compassion, derived from the Buddhist deity Avalokiteshvara and widely venerated in Japan.
-
E.
Nonsan
Nonsan is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
- 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-CAI Triple: [GOSAT, instrument, TANSO-CAI]
Generated description
TANSO-CAI is a satellite-borne imaging instrument on Japan’s GOSAT mission designed to monitor clouds and aerosols to support greenhouse gas observations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TANSO-CAI Target entity description: TANSO-CAI is a satellite-borne imaging instrument on Japan’s GOSAT mission designed to monitor clouds and aerosols to support greenhouse gas observations.
-
A.
Tunechi
Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
-
B.
TOICA
TOICA is a rechargeable contactless smart card used for fare payment on trains and buses in the Nagoya area and other parts of Japan’s JR Central network.
-
C.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
-
D.
Kannon
Kannon is the Japanese name for the bodhisattva of compassion, derived from the Buddhist deity Avalokiteshvara and widely venerated in Japan.
-
E.
Nonsan
Nonsan is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
- 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.