Triple
T18077788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-132 |
E432601
|
entity |
| Predicate | visitedISSModule |
P99686
|
FINISHED |
| Object | Zvezda |
—
|
NE NERFINISHED |
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: Zvezda | Statement: [STS-132, visitedISSModule, Zvezda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zvezda Context triple: [STS-132, visitedISSModule, Zvezda]
-
A.
Zvezda
chosen
Zvezda is a Russian-built service module of the International Space Station that provides life support, living quarters, and key control systems for the station.
-
B.
Starshina
Starshina was a senior non-commissioned officer rank in the Soviet military, roughly equivalent to a master sergeant and typically responsible for unit administration and discipline.
-
C.
Yıldız
Yıldız is a Turkish feminine given name meaning "star," commonly used in Turkey and among Turkish-speaking communities.
-
D.
Kozmodemyansk
Kozmodemyansk is a historic town in the Mari El Republic of Russia, situated on the Volga River and known for its traditional Mari culture and wooden architecture.
-
E.
Aelita
Aelita is a pioneering early Soviet science fiction novel by Alexei Tolstoy that tells the story of a journey to Mars and a revolutionary uprising there.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:26 a.m.