Triple
T21256342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-101 |
E523878
|
entity |
| Predicate | visitedISSModule |
P99686
|
FINISHED |
| Object | Zarya |
—
|
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: Zarya | Statement: [STS-101, visitedISSModule, Zarya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zarya Context triple: [STS-101, visitedISSModule, Zarya]
-
A.
Zarya
chosen
Zarya is the first module of the International Space Station, providing initial power, propulsion, and guidance functions for the orbiting laboratory.
-
B.
Zarya
Zarya is a powerful, pink-haired Russian soldier and tank hero in the video game Overwatch, known for her particle cannon, protective barriers, and high-damage potential when charged.
-
C.
Zarya
Zarya was a 19th-century Russian literary journal that published notable works by authors such as Fyodor Dostoevsky.
-
D.
Albatros D.Va
The Albatros D.Va was a late-World War I German single-seat fighter biplane used by the Luftstreitkräfte, known for its streamlined wooden monocoque fuselage and service with notable aces despite structural weaknesses.
-
E.
D.Va
D.Va is a popular hero from the game Overwatch, known as a former pro gamer who pilots a high-tech mech in fast-paced combat.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735a1f9e08190b494f582bcae5c35 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:58 p.m.