Triple
T15297129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarzan (2013 film) |
E365688
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object |
Craig Garner
Craig Garner is a voice actor known for his work in the 2013 animated film "Tarzan."
|
E1148120
|
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: Craig Garner | Statement: [Tarzan (2013 film), voiceActor, Craig Garner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Garner Context triple: [Tarzan (2013 film), voiceActor, Craig Garner]
-
A.
Guy Darrin Gardner
Guy Darrin Gardner is a fictional DC Comics superhero best known as the brash and hot-headed Green Lantern of Earth.
-
B.
Len Garry
Len Garry is a British musician best known as the original tea-chest bass player in The Quarrymen, the skiffle group that evolved into The Beatles.
-
C.
Sid Garner
Sid Garner is a fictional character from "The Hangover" film series, known as the wealthy and often exasperated father-in-law of Doug Billings.
-
D.
Linton Garner
Linton Garner was an American jazz pianist and composer known for his work as a sideman and arranger, and as the older brother of famed pianist Erroll Garner.
-
E.
Trevor Gardner
Trevor Gardner was a prominent U.S. defense official and aerospace executive known for his influential role in advancing American missile and space programs during the Cold War.
- 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: Craig Garner Triple: [Tarzan (2013 film), voiceActor, Craig Garner]
Generated description
Craig Garner is a voice actor known for his work in the 2013 animated film "Tarzan."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Craig Garner Target entity description: Craig Garner is a voice actor known for his work in the 2013 animated film "Tarzan."
-
A.
Guy Darrin Gardner
Guy Darrin Gardner is a fictional DC Comics superhero best known as the brash and hot-headed Green Lantern of Earth.
-
B.
Len Garry
Len Garry is a British musician best known as the original tea-chest bass player in The Quarrymen, the skiffle group that evolved into The Beatles.
-
C.
Sid Garner
Sid Garner is a fictional character from "The Hangover" film series, known as the wealthy and often exasperated father-in-law of Doug Billings.
-
D.
Linton Garner
Linton Garner was an American jazz pianist and composer known for his work as a sideman and arranger, and as the older brother of famed pianist Erroll Garner.
-
E.
Trevor Gardner
Trevor Gardner was a prominent U.S. defense official and aerospace executive known for his influential role in advancing American missile and space programs during the Cold War.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e036848c1881908fbaaae0216d6d27 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef82f6d08190b809260dda247dfe |
completed | May 9, 2026, 8:25 a.m. |
| NEDg | Description generation | batch_69fef08efec88190a66159ba39409ec9 |
completed | May 9, 2026, 8:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fef1715c3081909bddb24688c810a7 |
completed | May 9, 2026, 8:33 a.m. |
Created at: April 10, 2026, 3:15 a.m.