Triple
T35604265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1988 Cannes Film Festival (out of competition) |
E1028840
|
entity |
| Predicate | countryOfFestivalOrganizer |
P10523
|
FINISHED |
| Object | France |
E861
|
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: France | Statement: [1988 Cannes Film Festival (out of competition), countryOfFestivalOrganizer, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfFestivalOrganizer Context triple: [1988 Cannes Film Festival (out of competition), countryOfFestivalOrganizer, France]
-
A.
organizerCountry
chosen
Indicates the country that serves as the organizer or host for an event, activity, or initiative.
-
B.
festivalCountry
Indicates the country in which a given festival takes place or is held.
-
C.
countryOfVenue
Indicates the country in which the referenced venue is geographically located.
-
D.
locationCountryOfCeremony
Indicates the country in which a particular ceremony takes place or is held.
-
E.
countryOfShow
Indicates that a show is associated with, produced in, or originates from a particular country.
- F. None of above.
Provenance (4 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_69f76e0653ec81909b1b813c126c6574 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a01e3a2d0e08190a7d5622920dc56e6 |
completed | May 11, 2026, 2:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38683979d48190a65f98eed4c71828 |
completed | June 21, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_6a01e3013e7881909f0cdca25a53c009 |
completed | May 11, 2026, 2:09 p.m. |
Created at: May 3, 2026, 4:05 p.m.