Triple
T168678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koreatown (Manhattan) |
E3070
|
entity |
| Predicate | languageVisibleOnSignage |
P4196
|
FINISHED |
| Object | Korean |
—
|
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: Korean | Statement: [Koreatown (Manhattan), languageVisibleOnSignage, Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageVisibleOnSignage Context triple: [Koreatown (Manhattan), languageVisibleOnSignage, Korean]
-
A.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
-
B.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
C.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
D.
presentedInLanguage
Indicates that something (such as content, information, or a work) is expressed or made available using a particular language.
-
E.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b6f4f88190b1264bbbeb19a29e |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25665f5b8819096ca3e084faf976e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.