Triple
T7834928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spartan-Halley free-flyer |
E181666
|
entity |
| Predicate | target |
P860
|
FINISHED |
| Object | 1P/Halley |
E229500
|
NE FINISHED |
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: 1P/Halley | Statement: [Spartan-Halley free-flyer, target, 1P/Halley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 1P/Halley Context triple: [Spartan-Halley free-flyer, target, 1P/Halley]
-
A.
Dibiasky comet
The Dibiasky comet is the fictional, Earth-destroying comet central to the plot of the satirical disaster film "Don't Look Up."
-
B.
Halley
chosen
Halley is the surname of the English astronomer and mathematician Edmund Halley, best known for computing the orbit of the periodic comet that now bears his name.
-
C.
Komet
Komet was the nickname of the Messerschmitt Me 163, a German World War II rocket-powered interceptor aircraft known for its extraordinary speed and unconventional design.
-
D.
Comet
Comet is one of Santa Claus’s traditional flying reindeer, often depicted as swift and spirited as he helps pull Santa’s sleigh on Christmas Eve.
-
E.
Comet
Comet is a U.S. digital broadcast television network specializing in science fiction, fantasy, and horror programming.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064b872081908e269f4fe1b85436 |
completed | March 30, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5aa3f75881908e5380b5d8f86ea6 |
completed | March 31, 2026, 5:24 a.m. |
Created at: March 30, 2026, 4:45 p.m.