Triple
T17426641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mobile Asteroid Surface Scout |
E423754
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | MASCOT |
—
|
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: MASCOT | Statement: [Mobile Asteroid Surface Scout, shortName, MASCOT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MASCOT Context triple: [Mobile Asteroid Surface Scout, shortName, MASCOT]
-
A.
MASCOT
chosen
MASCOT is a small German-French-built lander that accompanied Japan’s Hayabusa2 mission to explore and study the surface of asteroid Ryugu.
-
B.
Mascot
Mascot is an inner-southern suburb of Sydney, Australia, best known for being home to the city's major international airport.
-
C.
Mascot
Mascot is a small unincorporated community in eastern Knox County, Tennessee, known historically for its ties to mining and quarry operations.
-
D.
Mascots
Mascots is a 2016 mockumentary comedy film directed by Christopher Guest that follows the quirky competitors in a global mascot competition.
-
E.
Mascot Corporal
Mascot Corporal is a Texas A&M University student position responsible for caring for and presenting the school’s official mascot, Reveille, at events and ceremonies.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e448fcbf54819091babed0b9b05716 |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.