Triple
T381795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telluride Film Festival |
E8695
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
TFF
TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
|
E48005
|
NE FINISHED |
How this triple was built (4 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: TFF | Statement: [Telluride Film Festival, alsoKnownAs, TFF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TFF Context triple: [Telluride Film Festival, alsoKnownAs, TFF]
-
A.
FTTA
FTTA is a U.S. law that promotes collaboration and technology transfer between federal laboratories and the private sector to commercialize government-funded innovations.
-
B.
TFI
TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
-
C.
AFC
The AFC (American Football Conference) is one of the two conferences that make up the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
-
D.
AFC
The AFC (Asian Football Confederation) is the governing body for association football in Asia, overseeing international competitions and member associations across the continent.
-
E.
TRT
TRT is the time zone used in Turkey, corresponding to UTC+3.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TFF Triple: [Telluride Film Festival, alsoKnownAs, TFF]
Generated description
TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TFF Target entity description: TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
-
A.
FTTA
FTTA is a U.S. law that promotes collaboration and technology transfer between federal laboratories and the private sector to commercialize government-funded innovations.
-
B.
TFI
TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
-
C.
AFC
The AFC (American Football Conference) is one of the two conferences that make up the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
-
D.
AFC
The AFC (Asian Football Confederation) is the governing body for association football in Asia, overseeing international competitions and member associations across the continent.
-
E.
TRT
TRT is the time zone used in Turkey, corresponding to UTC+3.
- F. None of above. chosen
Provenance (5 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2e3d5c8190b358bd9fd6b16a14 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3fb0100fc8190819b977bb7a98d7f |
completed | March 1, 2026, 8:38 a.m. |
| NEDg | Description generation | batch_69a3fb6569e881909d52f07a4207ed24 |
completed | March 1, 2026, 8:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3fbdfdfcc81909ae03736623594d5 |
completed | March 1, 2026, 8:42 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.