Triple
T33771462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poppy Land |
E865392
|
entity |
| Predicate | countryInRealWorldFilming |
P21831
|
FINISHED |
| Object | Italy |
—
|
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: Italy | Statement: [Poppy Land, countryInRealWorldFilming, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryInRealWorldFilming Context triple: [Poppy Land, countryInRealWorldFilming, Italy]
-
A.
countryOfFilming
chosen
Indicates the country where the filming or production of a work physically took place.
-
B.
countryInReality
Indicates that a given country exists or is recognized as such within a particular real-world context or scenario.
-
C.
filmingCountry
Indicates the country where the filming or primary production of a work took place.
-
D.
filmingRegions
Indicates the geographic areas or locations where the filming or production of a work takes place.
-
E.
countryOfCinematicActivity
Indicates the country in which a person or entity is primarily active or recognized in the field of cinema.
- F. None of above.
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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00d08e8fac8190b59359134e6e1c03 |
completed | May 10, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_6a00d0127c088190a6f5b360450af113 |
completed | May 10, 2026, 6:36 p.m. |
Created at: May 1, 2026, 1:45 a.m.