Triple
T25054240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metro Marunouchi Line (at Ikebukuro Station) |
E627469
|
entity |
| Predicate | signageCodeColor |
P50252
|
FINISHED |
| Object | red (Marunouchi Line color) |
—
|
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: red (Marunouchi Line color) | Statement: [Tokyo Metro Marunouchi Line (at Ikebukuro Station), signageCodeColor, red (Marunouchi Line color)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signageCodeColor Context triple: [Tokyo Metro Marunouchi Line (at Ikebukuro Station), signageCodeColor, red (Marunouchi Line color)]
-
A.
signageTextColor
Indicates the color used for the text displayed on a sign.
-
B.
usesSignageColorSystem
Indicates that an entity employs a specific color-based signage system to convey information, instructions, or guidance.
-
C.
hasNationalSignageColor
Indicates that an entity uses a particular color (or set of colors) as its officially designated national signage color scheme.
-
D.
signatureColor
chosen
Indicates that an entity has a characteristic or defining color that is uniquely or primarily associated with it.
-
E.
roadSignColor
Indicates the color attribute associated with a particular road sign.
- 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:09 a.m.