Triple
T7430695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Underground Metropolitan line |
E171480
|
entity |
| Predicate | lineColourHex |
P34402
|
FINISHED |
| Object | #9B0056 |
—
|
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: #9B0056 | Statement: [London Underground Metropolitan line, lineColourHex, #9B0056]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineColourHex Context triple: [London Underground Metropolitan line, lineColourHex, #9B0056]
-
A.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
B.
lineLetterColorStandard
Indicates the standard or default color assigned to the letter representation of a particular line.
-
C.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
-
D.
threadColor
Indicates the color associated with a particular thread.
-
E.
colorLineContext
Indicates a relationship where the color of a line is determined or interpreted based on its surrounding contextual information or environment.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f32324c481908c9ba594e8456728 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.