Triple
T7164210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Amos |
E167025
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Admiral Grant
Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
|
E645468
|
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: Admiral Grant | Statement: [John Amos, playedCharacter, Admiral Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Admiral Grant Context triple: [John Amos, playedCharacter, Admiral Grant]
-
A.
Admiral Shane
Admiral Shane is a high-ranking U.S. Navy officer and key military leader in the science fiction action film "Battleship."
-
B.
Admiral James Buck
Admiral James Buck was a United States Navy flag officer honored for his service by having the destroyer USS Buck (DD-420) named after him.
-
C.
Admiral James Greer
Admiral James Greer is a high-ranking U.S. Navy intelligence officer and mentor to analyst Jack Ryan in Tom Clancy’s techno-thriller universe, notably featured in "The Hunt for Red October."
-
D.
Captain Vidal
Captain Vidal is the ruthless and authoritarian Falangist officer who serves as the primary antagonist in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
E.
Admiral William Brown
Admiral William Brown was an Irish-born Argentine naval officer who is celebrated as the founder and first admiral of the Argentine Navy.
- 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: Admiral Grant Triple: [John Amos, playedCharacter, Admiral Grant]
Generated description
Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Admiral Grant Target entity description: Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
-
A.
Admiral Shane
Admiral Shane is a high-ranking U.S. Navy officer and key military leader in the science fiction action film "Battleship."
-
B.
Admiral James Buck
Admiral James Buck was a United States Navy flag officer honored for his service by having the destroyer USS Buck (DD-420) named after him.
-
C.
Admiral James Greer
Admiral James Greer is a high-ranking U.S. Navy intelligence officer and mentor to analyst Jack Ryan in Tom Clancy’s techno-thriller universe, notably featured in "The Hunt for Red October."
-
D.
Captain Vidal
Captain Vidal is the ruthless and authoritarian Falangist officer who serves as the primary antagonist in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
E.
Admiral William Brown
Admiral William Brown was an Irish-born Argentine naval officer who is celebrated as the founder and first admiral of the Argentine Navy.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e83168a08190937ff46797d94f3e |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adcc145c8190ba65831ed891a225 |
completed | March 28, 2026, 10:30 a.m. |
| NEDg | Description generation | batch_69c7ae9111048190b9d68932b15aeab9 |
completed | March 28, 2026, 10:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7af44076481908d770dd92ed55277 |
completed | March 28, 2026, 10:36 a.m. |
Created at: March 27, 2026, 2:47 p.m.