Triple
T2208352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French autoroute network |
E50854
|
entity |
| Predicate | signageTextColor |
P37450
|
FINISHED |
| Object | white |
—
|
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: white | Statement: [French autoroute network, signageTextColor, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signageTextColor Context triple: [French autoroute network, signageTextColor, white]
-
A.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
B.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
-
C.
logoColor
Indicates the color or primary color scheme used in an entity’s logo.
-
D.
serialNumberColor
Indicates a relationship where a specific serial number is associated with a particular color.
-
E.
lineLetterColorStandard
Indicates the standard or default color assigned to the letter representation of a particular line.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc1b912c08190b9d7bc9230e49d1d |
completed | March 7, 2026, 6:12 a.m. |
Created at: March 4, 2026, 7:46 p.m.