Triple
T26634462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille (pun on Lou Seal) |
E668595
|
entity |
| Predicate | usesHomophony |
P119509
|
FINISHED |
| Object | Lou / Lu |
—
|
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: Lou / Lu | Statement: [Lucille (pun on Lou Seal), usesHomophony, Lou / Lu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesHomophony Context triple: [Lucille (pun on Lou Seal), usesHomophony, Lou / Lu]
-
A.
hasHomophones
chosen
Indicates that two or more linguistic expressions share the same pronunciation but differ in meaning, spelling, or both.
-
B.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
C.
heteronymOf
Indicates that two words share the same spelling but differ in pronunciation and meaning.
-
D.
heteronym
Indicates that two or more words share the same spelling but differ in pronunciation and meaning.
-
E.
hasDistinctLetterForSound
Indicates that a particular sound is represented by its own unique letter, distinct from other sounds in the writing system.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 2:26 a.m.