Triple
T10738812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gazelle |
E253264
|
entity |
| Predicate | antagonistOf |
P18963
|
FINISHED |
| Object | Eggsy Unwin |
E49510
|
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: Eggsy Unwin | Statement: [Gazelle, antagonistOf, Eggsy Unwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eggsy Unwin Context triple: [Gazelle, antagonistOf, Eggsy Unwin]
-
A.
Gary "Eggsy" Unwin
chosen
Gary "Eggsy" Unwin is a street-smart British youth who becomes a highly skilled gentleman spy in the Kingsman film series.
-
B.
Harvey Ackroyd
Harvey Ackroyd was an architect known for his work on the Tennessee State Capitol.
-
C.
Jack Kitchin
Jack Kitchin was a film editor known for his work on early Hollywood productions, including classic musicals of the 1930s.
-
D.
Charles Butterworth
Charles Butterworth was an American comic film actor of the 1930s and early 1940s, known for his dry, dithering persona in numerous Hollywood comedies.
-
E.
David Eggby
David Eggby is an Australian cinematographer known for his work on genre films, including the live-action Scooby-Doo (2002) and the original Mad Max.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710424d8c81908ee9b59d622f2af5 |
completed | April 9, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de22ed6edc8190beb76bd2971c7cec |
completed | April 14, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:14 p.m.