Triple
T6031026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph 124C 41+ |
E134301
|
entity |
| Predicate | titlePunningOn |
P36401
|
FINISHED |
| Object | phrase "one to foresee for one" |
—
|
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: phrase "one to foresee for one" | Statement: [Ralph 124C 41+, titlePunningOn, phrase "one to foresee for one"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titlePunningOn Context triple: [Ralph 124C 41+, titlePunningOn, phrase "one to foresee for one"]
-
A.
hasTitlePun
chosen
Indicates that an entity’s title involves a pun or wordplay, typically combining multiple meanings or sounds for humorous or clever effect.
-
B.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
-
C.
titlePunctuation
Indicates that a title includes specific punctuation marks or follows a particular punctuation pattern.
-
D.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
E.
titleRepresents
Indicates that a given title stands for, denotes, or symbolizes a particular concept, role, work, or 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056af89e881909652957f94317684 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:08 p.m.