Triple
T18139970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samba |
E434234
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Youngar Fall
Youngar Fall is an actor known for appearing in the film "Samba."
|
E1307918
|
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: Youngar Fall | Statement: [Samba, castMember, Youngar Fall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Youngar Fall Context triple: [Samba, castMember, Youngar Fall]
-
A.
Reversing Falls
Reversing Falls is a set of powerful rapids and whirlpools near Saint John, New Brunswick, where the tidal forces of the Bay of Fundy dramatically reverse the flow of the river.
-
B.
Mama Falls
Mama Falls is one of the twin waterfalls at Trafalgar Falls in Dominica, known for its tall, narrow cascade set amid lush tropical rainforest.
-
C.
The Mighty Fall
The Mighty Fall is a musical project or band connected to drummer Jonny Quinn, best known for his work with the rock band Snow Patrol.
-
D.
Sunfall
Sunfall is a science-based dystopian thriller novel by physicist and author Jim Al-Khalili that explores the catastrophic consequences of a collapsing Earth magnetic field.
-
E.
Stationfall
Stationfall is a 1987 interactive fiction comedy-adventure game by Infocom and a sequel to the earlier title Planetfall.
- 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: Youngar Fall Triple: [Samba, castMember, Youngar Fall]
Generated description
Youngar Fall is an actor known for appearing in the film "Samba."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Youngar Fall Target entity description: Youngar Fall is an actor known for appearing in the film "Samba."
-
A.
Reversing Falls
Reversing Falls is a set of powerful rapids and whirlpools near Saint John, New Brunswick, where the tidal forces of the Bay of Fundy dramatically reverse the flow of the river.
-
B.
Mama Falls
Mama Falls is one of the twin waterfalls at Trafalgar Falls in Dominica, known for its tall, narrow cascade set amid lush tropical rainforest.
-
C.
The Mighty Fall
The Mighty Fall is a musical project or band connected to drummer Jonny Quinn, best known for his work with the rock band Snow Patrol.
-
D.
Sunfall
Sunfall is a science-based dystopian thriller novel by physicist and author Jim Al-Khalili that explores the catastrophic consequences of a collapsing Earth magnetic field.
-
E.
Stationfall
Stationfall is a 1987 interactive fiction comedy-adventure game by Infocom and a sequel to the earlier title Planetfall.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de0a59d08190be74c1ecc00a8f3a |
completed | April 19, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03854e76d8819082bae8d5f08e5992 |
completed | May 12, 2026, 7:53 p.m. |
| NEDg | Description generation | batch_6a038684e2908190ad31b29faabb4e46 |
completed | May 12, 2026, 7:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0386e3b51c81908c41fa719a4bf72f |
completed | May 12, 2026, 8 p.m. |
Created at: April 10, 2026, 10:29 a.m.