Triple
T2425497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cane |
E53515
|
entity |
| Predicate | containsCharacter |
P5716
|
FINISHED |
| Object | Fern |
E243963
|
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: Fern | Statement: [Cane, containsCharacter, Fern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fern Context triple: [Cane, containsCharacter, Fern]
-
A.
Fern
chosen
Fern is the middle-aged, van-dwelling woman at the heart of the film "Nomadland," whose journey through the American West explores themes of loss, resilience, and modern nomadic life.
-
B.
Tamsin
Tamsin is a feminine given name of English origin, often associated with actresses and public figures such as Tamsin Egerton.
-
C.
Fiona
Fiona is an American singer-songwriter and pianist known for her emotionally intense, critically acclaimed alternative music.
-
D.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
-
E.
Dora Riparia
Dora Riparia is a river in northwestern Italy that flows through the city of Turin before joining the Po River.
- 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc99a773c819092d5f3c297b83887 |
completed | March 7, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf61088481909d79e822e4071456 |
completed | March 9, 2026, 12:38 p.m. |
Created at: March 6, 2026, 9:42 p.m.