Triple
T20892267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thor’s Helmet Nebula |
E514436
|
entity |
| Predicate | belongsToCatalogue |
P19933
|
FINISHED |
| Object | Gum catalogue |
—
|
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: Gum catalogue | Statement: [Thor’s Helmet Nebula, belongsToCatalogue, Gum catalogue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gum catalogue Context triple: [Thor’s Helmet Nebula, belongsToCatalogue, Gum catalogue]
-
A.
GUM
GUM is a historic and iconic department store located on Red Square in Moscow, Russia, known for its grand architecture and luxury retail offerings.
-
B.
GUM
GUM is the IATA airport code for Antonio B. Won Pat International Airport, the main commercial airport serving Guam in the western Pacific.
-
C.
Gum
Gum is a stylish, graffiti-tagging inline skater and one of the main playable members of the GGs gang in the Jet Set Radio video game series.
-
D.
Gum
chosen
Gum is an astronomical catalog compiled by Australian astronomer Colin Stanley Gum that lists emission nebulae in the southern sky.
-
E.
5 Gum
5 Gum is a popular sugar-free chewing gum brand known for its intense flavors and sleek, modern packaging aimed at teens and young adults.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d05f0bec8190a296db546bd34114 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.