Triple
T35225910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlonn |
E1017092
|
entity |
| Predicate | hasStressPatternSimilarTo |
P4253
|
FINISHED |
| Object | Marlon |
—
|
NE NERFINISHED |
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: Marlon | Statement: [Marlonn, hasStressPatternSimilarTo, Marlon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStressPatternSimilarTo Context triple: [Marlonn, hasStressPatternSimilarTo, Marlon]
-
A.
hasStressPattern
chosen
Indicates that an entity (such as a word or phrase) follows a particular arrangement of stressed and unstressed units (e.g., syllables) in its pronunciation.
-
B.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
C.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
-
D.
hasLexicalSimilarityWith
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
-
E.
hasNotableMelodicSimilarityTo
Indicates that one musical piece shares a clearly recognizable and significant similarity in melody with another.
- 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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffde9263248190996f970b6cf6e49d |
completed | May 10, 2026, 1:25 a.m. |
| PD | Predicate disambiguation | batch_69ffdd760f1c8190abc6c0c1cd97ba5f |
completed | May 10, 2026, 1:20 a.m. |
Created at: May 3, 2026, 4:02 p.m.