Triple
T20306630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Doll Posse |
E510124
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Dragon |
—
|
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: Dragon | Statement: [American Doll Posse, hasPart, Dragon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dragon Context triple: [American Doll Posse, hasPart, Dragon]
-
A.
Dragon
Dragon is the NATO reporting name for the Saab 35 Draken, a Swedish Cold War-era supersonic fighter aircraft known for its distinctive double-delta wing design.
-
B.
Dragon
chosen
Dragon is a powerful, fire-breathing dragon character from the Shrek franchise who initially guards Princess Fiona’s tower and later becomes Donkey’s love interest.
-
C.
Dragon
Dragon is SpaceX’s reusable spacecraft designed to transport cargo and crew to and from orbit, including missions to the International Space Station.
-
D.
Dragon
Dragon is a legendary mythical creature, typically depicted as a large, powerful, winged reptile capable of breathing fire and appearing in the folklore of many cultures worldwide.
-
E.
Drac
The Drac is a river in southeastern France that flows through the Alps and is a significant tributary of the Isère.
- 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6774068c08190824fa55438bab712 |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:18 a.m.