Triple
T3327637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama Chinatown |
E69953
|
entity |
| Predicate | scriptUsedInSignage |
P47313
|
FINISHED |
| Object | Kanji |
—
|
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: Kanji | Statement: [Yokohama Chinatown, scriptUsedInSignage, Kanji]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptUsedInSignage Context triple: [Yokohama Chinatown, scriptUsedInSignage, Kanji]
-
A.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
B.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
C.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
D.
scriptOnFlag
Indicates that a script is attached to and/or executed when a specific flag or condition is set.
-
E.
scriptUsedCurrently
Indicates that a particular writing system or script is the one presently in use for a given language, text, or context.
- F. None of above. chosen
Provenance (4 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb16f61248190bab10f4ac9e066f7 |
completed | March 8, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69ada42a19348190a3862ce02451f4aa |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada52716ec81908e89688a81039394 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:12 p.m.