Triple
T14711232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Swan |
E345551
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Swan |
E280999
|
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: Swan | Statement: [Bella Swan, familyName, Swan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swan Context triple: [Bella Swan, familyName, Swan]
-
A.
Swan
chosen
Swan is a large, graceful waterbird known for its long neck, white or black plumage, and strong cultural associations with beauty and elegance.
-
B.
Swan
Swan is a small city in Marion County, Iowa, United States.
-
C.
Swan
Swan is the charismatic yet sinister music producer and antagonist in the rock-horror film "Phantom of the Paradise."
-
D.
Balloon Swan
Balloon Swan is a sculptural artwork resembling a swan made from a twisted balloon, created as part of the artist’s Celebration series.
-
E.
Swan King
Swan King is the romantic nickname of Ludwig II of Bavaria, the 19th-century monarch famed for his fairy-tale castles and patronage of composer Richard Wagner.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb9814e0c8190984ac30d276499cc |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf08f2aa08190a5ac3240d1de90fb |
completed | May 8, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:28 a.m.