Triple
T18077793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-132 |
E432601
|
entity |
| Predicate | visitedISSModule |
P99686
|
FINISHED |
| Object | Kibo |
—
|
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: Kibo | Statement: [STS-132, visitedISSModule, Kibo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kibo Context triple: [STS-132, visitedISSModule, Kibo]
-
A.
Kibo
chosen
Kibo is Japan’s primary science module on the International Space Station, used for a wide range of microgravity experiments and technology demonstrations.
-
B.
Mount Kilimanjaro
Mount Kilimanjaro is a massive dormant stratovolcano in northeastern Tanzania and the tallest mountain in Africa, famed for its snow-capped summit rising above the surrounding savanna.
-
C.
Kili
Kili is a young Dwarf prince of Durin's line and a member of Thorin Oakenshield's company in J.R.R. Tolkien's Middle-earth legendarium.
-
D.
Mount Tambuyukon
Mount Tambuyukon is a high, biodiverse mountain in Sabah, Malaysian Borneo, known for its rich montane ecosystems and rare endemic species.
-
E.
Kibo summit crater
Kibo summit crater is the large volcanic crater at the highest point of Mount Kilimanjaro in Tanzania, forming the mountain’s main summit area.
- 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.