Triple
T23672292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamu |
E584762
|
entity |
| Predicate | hasTitleInEnglishTransliteration |
P46856
|
FINISHED |
| Object | Mamu |
—
|
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: Mamu | Statement: [Mamu, hasTitleInEnglishTransliteration, Mamu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInEnglishTransliteration Context triple: [Mamu, hasTitleInEnglishTransliteration, Mamu]
-
A.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
B.
hasTitleInTransliteration
chosen
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
C.
hasTitleInLanguage
Indicates that an entity has a specific title expressed in a particular language.
-
D.
hasTitleInRevisedRomanization
Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
-
E.
hasApproximateEnglishTitle
Indicates that an entity is associated with an English title that is an approximate or non-exact rendering of its original title.
- 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_69e24901421881908c17a5293bdd4a8e |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b41002f881908cd744ed44b70f5d |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.