Triple
T14338538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christ with raised arms |
E355528
|
entity |
| Predicate | popularNicknameReason |
P7596
|
FINISHED |
| Object | resembles a football referee’s touchdown signal |
—
|
LITERAL 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: resembles a football referee’s touchdown signal | Statement: [Christ with raised arms, popularNicknameReason, resembles a football referee’s touchdown signal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularNicknameReason Context triple: [Christ with raised arms, popularNicknameReason, resembles a football referee’s touchdown signal]
-
A.
reasonForNickname
chosen
Indicates the explanation or cause behind why a particular nickname was given to an entity.
-
B.
nicknamedFor
Indicates that one entity serves as the source, inspiration, or reason for another entity’s nickname.
-
C.
popularName
Indicates that the object is a commonly used or widely recognized name or nickname for the subject.
-
D.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
E.
unofficialNickname
Indicates that one entity is informally or colloquially known by a non-official nickname represented by the other entity.
- F. None of above.
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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e8674c0819091dfbe9c50778c5e |
completed | April 14, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.