Triple
T4065677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GOSAT-2 |
E86316
|
entity |
| Predicate | instrument |
P792
|
FINISHED |
| Object | TANSO-FTS-2 |
E410454
|
NE FINISHED |
How this triple was built (2 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-2 | Statement: [GOSAT-2, instrument, TANSO-FTS-2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TANSO-FTS-2 Context triple: [GOSAT-2, instrument, TANSO-FTS-2]
-
A.
TANSO-FTS
chosen
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.
-
B.
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.
-
C.
NTT 3.58 m Telescope
The NTT 3.58 m Telescope is a pioneering European Southern Observatory instrument at La Silla that introduced active optics technology for high-precision astronomical observations.
-
D.
Turbostar
Turbostar is a family of modern British diesel multiple-unit trains widely used for regional and commuter services across the UK rail network.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69b56b55b5388190a90551c43388f3fc |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:38 p.m.